{"id":"W7130719356","doi":"10.6084/m9.figshare.28545184","title":"Additional file 1 of Cross-validation for training and testing co-occurrence network inference algorithms","year":2025,"lang":"","type":"article","venue":"Figshare","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Training (meteorology); Inference; Training set; Artificial neural network; Table (database); Key (lock)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002684848,0.002141622,0.001443297,0.002256502,0.0008393991,0.001729256,0.003173686,0.001753493,0.8661683],"category_scores_gemma":[0.05054715,0.0008239127,0.00118485,0.002540514,0.0004647153,0.001766905,0.001271263,0.001574798,0.339758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006895593,"about_ca_system_score_gemma":0.001387663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003950393,"about_ca_topic_score_gemma":0.009508329,"domain_scores_codex":[0.9989389,0.0002891512,0.0001340096,0.0003391164,0.0002046652,0.00009420062],"domain_scores_gemma":[0.9590248,0.03470631,0.0004920389,0.002338757,0.003067067,0.0003710483],"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":[0.0002930971,0.0001094543,0.001013936,0.001348458,0.00006079159,0.00004596827,0.00002830247,0.001609514,0.0001587892,0.0005252436,0.9768047,0.01800183],"study_design_scores_gemma":[0.005178994,0.0007379278,0.01540532,0.002177425,0.0003506342,0.0007440999,0.000278339,0.02895058,0.004960404,0.03131381,0.9095919,0.00031057],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005424726,0.00004751312,0.004259344,0.00007550832,0.00009166197,0.0001448597,0.988813,0.004212166,0.001813412],"genre_scores_gemma":[0.01132412,0.00009790964,0.02088071,0.0003535169,0.0001312239,0.002546228,0.9451074,0.008620084,0.0109388],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8661683,"threshold_uncertainty_score":0.1908947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1512515939328451,"score_gpt":0.3592783586928253,"score_spread":0.2080267647599802,"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."}}