{"id":"W4231542127","doi":"10.1109/tce.2020.2964888","title":"IEEE Consumer Electronics Society Board of Governors","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Consumer Electronics","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Electronics; Electrical engineering; Engineering; Telecommunications; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001222814,0.0002722914,0.0003071633,0.00006275185,0.0001625337,0.00006359896,0.0006544998,0.0001341224,0.0000357187],"category_scores_gemma":[0.000008793617,0.0002977647,0.0002948819,0.0006520345,0.00007674438,0.0002429193,0.000004151438,0.000669155,0.00007178195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002244636,"about_ca_system_score_gemma":0.0007375883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002701638,"about_ca_topic_score_gemma":0.00003596744,"domain_scores_codex":[0.9980537,0.00003497426,0.0003916874,0.0004698203,0.0004370111,0.0006127758],"domain_scores_gemma":[0.9988426,0.0002029298,0.0001183468,0.0004626706,0.0001558165,0.0002176155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000195043,0.001773729,0.0003651649,0.0005068252,0.003024623,0.00001434729,0.005592417,0.657273,0.1244075,0.06994131,0.03382363,0.1030825],"study_design_scores_gemma":[0.001771255,0.000918503,0.0001266002,0.00006929324,0.00028357,0.00003432504,0.00009699679,0.5705047,0.322832,0.0009769771,0.1010365,0.001349189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01317674,0.001758781,0.9815516,0.002333812,0.0005932968,0.0001859154,0.00002137958,0.0001901025,0.0001883965],"genre_scores_gemma":[0.9806415,0.002534569,0.01551016,0.001015365,0.00004667345,0.00002606259,0.000002864503,0.0000407485,0.0001820477],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9674648,"threshold_uncertainty_score":0.9999474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582685720654566,"score_gpt":0.230709903164994,"score_spread":0.2148830459584483,"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."}}