{"id":"W2969582440","doi":"","title":"Copycat Hand for All at Laval Virtual ReVolution 2009","year":2009,"lang":"en","type":"article","venue":"IEICE Technical Report; IEICE Tech. Rep.","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Copycat; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002315599,0.0005165965,0.0007262573,0.0002006188,0.0005230217,0.0003603979,0.001821398,0.0005369727,0.00001194633],"category_scores_gemma":[0.001243498,0.0004880203,0.0004328957,0.0008666788,0.0001749055,0.0004886584,0.0004558171,0.0005067057,0.000114625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004434597,"about_ca_system_score_gemma":0.0002700282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001203698,"about_ca_topic_score_gemma":0.00004079752,"domain_scores_codex":[0.9947428,0.0001246957,0.001505626,0.00158,0.0009960367,0.001050898],"domain_scores_gemma":[0.9954047,0.000433764,0.0009066738,0.002405626,0.0004475539,0.0004016353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003761434,0.001383995,0.0006902643,0.0001566323,0.0001753958,0.002491755,0.0003700656,0.001453589,0.1986109,0.07937495,0.6738544,0.04106192],"study_design_scores_gemma":[0.002273784,0.002756048,0.006100466,0.0004690913,0.0001577167,0.01072734,0.00002890158,0.01919921,0.01882791,0.01750878,0.9198511,0.002099711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02925407,0.0008551598,0.9520612,0.00431579,0.001168401,0.001582832,0.00004533171,0.003328391,0.007388866],"genre_scores_gemma":[0.96706,0.00003925402,0.02746414,0.0008739227,0.000438806,0.00009911742,0.0001319823,0.00003624036,0.003856489],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.937806,"threshold_uncertainty_score":0.9997572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941543550360342,"score_gpt":0.2908337394886804,"score_spread":0.271418303985077,"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."}}