{"id":"W3186531616","doi":"","title":"Grasping numbers: How numerical magnitude affects kinematics of reach to grasp actions","year":2018,"lang":"en","type":"article","venue":"URSCA Proceedings","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Mathematics; Block (permutation group theory); Set (abstract data type); Numeral system; Magnitude (astronomy); Object (grammar); Kinematics; Thumb; Arithmetic; Statistics; Artificial intelligence; Computer science; Geometry; Geology","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":[0.0006564651,0.0003967317,0.0004036035,0.0003509618,0.0001731295,0.001108358,0.0003237941,0.0004972919,0.008809914],"category_scores_gemma":[0.01444146,0.0004595323,0.0002194816,0.0001972123,0.0005998948,0.0009751563,0.000809676,0.0004452545,0.0007439577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000251081,"about_ca_system_score_gemma":0.0002941315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234133,"about_ca_topic_score_gemma":0.0009825446,"domain_scores_codex":[0.9992002,0.0002034932,0.00005998788,0.0002447969,0.0001891615,0.0001023177],"domain_scores_gemma":[0.9956881,0.002792011,0.0007790498,0.0002438932,0.0002131092,0.000283899],"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":[0.009977151,0.0005358625,0.02626289,0.0006645328,0.0001238423,0.0004508027,0.002015346,0.004809301,0.8851672,0.001631107,0.0007518322,0.06761006],"study_design_scores_gemma":[0.0004728367,0.004416594,0.8941724,0.000184681,0.0003215327,0.0007999344,0.0009534327,0.01803598,0.07125252,0.005617839,0.003640943,0.0001313071],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869112,0.0002759124,0.007288843,0.0001045362,0.00006282941,0.00006520321,0.0002288731,0.0001754328,0.004887085],"genre_scores_gemma":[0.9936538,0.0001052904,0.004236616,0.00003915276,0.00001165258,0.00007768811,0.0001246204,0.0001272955,0.001623986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008809914,"threshold_uncertainty_score":0.02947211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05338346932665444,"score_gpt":0.332677576827842,"score_spread":0.2792941075011875,"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."}}