{"id":"W2231865352","doi":"10.1016/j.cognition.2016.01.001","title":"The rules of tool incorporation: Tool morpho-functional & sensori-motor constraints","year":2016,"lang":"en","type":"article","venue":"Cognition","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Fédération pour la Recherche sur le Cerveau; Agence Nationale de la Recherche","keywords":"Kinematics; Morpho; Representation (politics); Thumb; Computer science; Index finger; GRASP; Object (grammar); Differential (mechanical device); Artificial intelligence; Physics; Anatomy; Biology; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007897444,0.0004456968,0.0005157182,0.0004149855,0.000779124,0.003041744,0.001365328,0.001435454,0.007106489],"category_scores_gemma":[0.003968687,0.0006231519,0.0005833952,0.0003802956,0.004186224,0.005391623,0.001516214,0.001899498,0.0009667727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006093514,"about_ca_system_score_gemma":0.0005756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001376408,"about_ca_topic_score_gemma":0.002121392,"domain_scores_codex":[0.9993494,0.0001165426,0.00005436617,0.0002283766,0.000179605,0.00007173406],"domain_scores_gemma":[0.9988256,0.0003872146,0.0001488589,0.0003741616,0.0001667093,0.000097495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001952682,0.0000662488,0.002371709,0.000215698,0.00005489731,0.0007758458,0.0004335309,0.01842032,0.06383553,0.8328607,0.003238729,0.0775316],"study_design_scores_gemma":[0.00003095037,0.00004871349,0.008125605,0.00004873357,0.00004160087,0.0008811689,0.0002633808,0.06673399,0.02421286,0.8869092,0.01261623,0.00008755076],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.21618,0.0009864913,0.5920846,0.002991167,0.0004887167,0.00008947894,0.0006704546,0.001077092,0.1854321],"genre_scores_gemma":[0.9347758,0.0002406108,0.05681162,0.0002197466,0.00003754666,0.00006349067,0.0001430876,0.0003710806,0.007337086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007106489,"threshold_uncertainty_score":0.02377355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04978526600185088,"score_gpt":0.2431749326623967,"score_spread":0.1933896666605458,"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."}}