{"id":"W4410049632","doi":"10.1101/2025.04.28.651066","title":"Action intentions result in the task-specific integration of object features","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Action (physics); Task (project management); Object (grammar); Computer science; Cognitive psychology; Psychology; Artificial intelligence; Engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001097906,0.0003315671,0.000329737,0.000847392,0.0001665981,0.0003986576,0.0005993774,0.0002931206,0.00002068622],"category_scores_gemma":[0.0004203747,0.0002810834,0.0001176755,0.001560155,0.00006467077,0.0005713581,0.0002895802,0.0006409214,0.00002354155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001502032,"about_ca_system_score_gemma":0.0002050679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001765278,"about_ca_topic_score_gemma":0.00008019693,"domain_scores_codex":[0.9980911,0.00006462137,0.0005711843,0.0005751576,0.0004416236,0.0002563328],"domain_scores_gemma":[0.9979531,0.00003833414,0.0005722202,0.0007327776,0.0006942333,0.000009377118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004299889,0.0009815107,0.0171296,0.002940476,0.000314373,0.00003362979,0.0002384754,0.0007274736,0.7978097,0.124632,0.05449703,0.0002657364],"study_design_scores_gemma":[0.001230421,0.00001444953,0.8637156,0.002121706,0.0002684892,1.772175e-8,0.000190584,0.001037446,0.06611811,0.0001810008,0.06394928,0.001172851],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703208,0.001965109,0.008271387,0.003944679,0.008807536,0.003541307,0.0001139178,0.0007408276,0.002294475],"genre_scores_gemma":[0.9976794,0.0002370439,0.0007356927,0.0003318074,0.0007808435,0.0001701468,0.000005610169,0.0000284033,0.00003103829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.846586,"threshold_uncertainty_score":0.9999641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02218148742325499,"score_gpt":0.2282131810546748,"score_spread":0.2060316936314198,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}