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concept:criterion-1-estimates-must-yield-80-good-cases-higher-score-higher-per-tom-task-to-indicate-potential-consciousnessCriterion 1: Φ estimates must yield >80% 'good' cases (higher score → higher Φ) per ToM task to indicate potential consciousness.
First of three operational criteria for identifying consciousness phenomena in LLM representations.
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- Criterion 2: Statistically significant Φ value differences (p<0.05) across ToM score categories via Wilcoxon test.associated_withSecond of three operational criteria; requires distributional significance in IIT estimates across performance levels.
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cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Specific prediction linking IIT's prediction of high Φ for good performance to the experimental design's scoring structure.
- Load-bearing epistemic caution the author places on the entire analytical framework.
- Even the rare cases where good > bad do not reach the 80% significance threshold required by Criterion 1.
- Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.claim0.775Central methodological claim of the paper.
- Paper's argument against behavioral tests for consciousness, establishing why MCH requires internal analysis
- Criterion 1 operationalization: requires >80% 'good' cases (higher score → higher Φ) per ToM task.
- Third of three operational criteria; distinguishes consciousness from inherent LLM representational separations.
- Do distinctions in Φ estimates remain robust across diverse ToM stimuli in repeated large-scale trials?question0.770Criterion 2 operationalization: requires p<0.05 in Wilcoxon tests across score categories.