{"id":"W6894155191","doi":"10.5683/sp3/fwrjqb","title":"ODRC data schema: Feed aggregation","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Raw data; Weight loss; Schema (genetic algorithms); Bin; Body weight; Data collection","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003165134,0.001605731,0.001172673,0.004352562,0.0008654688,0.005272163,0.002663965,0.001716425,0.08796314],"category_scores_gemma":[0.009297562,0.0009602985,0.001727671,0.008315302,0.0004645446,0.004176148,0.002719634,0.001709274,0.07304224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002839494,"about_ca_system_score_gemma":0.003395057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04199112,"about_ca_topic_score_gemma":0.03060634,"domain_scores_codex":[0.9967475,0.0003544935,0.0007455008,0.0008495532,0.001073725,0.0002293005],"domain_scores_gemma":[0.9932892,0.001083234,0.0004034235,0.001988578,0.003006738,0.0002288205],"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":[0.0001793222,0.00006709342,0.003569524,0.000898243,0.00006414255,0.00008430173,0.0002806509,0.001715942,0.0009946831,0.009364978,0.951165,0.03161598],"study_design_scores_gemma":[0.00002340033,0.000008308319,0.00149436,0.0001555173,0.00001365002,0.00005549705,0.0001435686,0.0007430991,0.0008098222,0.001797714,0.9947281,0.0000268623],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006774919,0.0001164947,0.01199812,0.0002980096,0.0001642188,0.0001953832,0.9625243,0.008551406,0.01547458],"genre_scores_gemma":[0.003821671,0.0002367533,0.01720945,0.0003693745,0.00003408554,0.0003810946,0.9704329,0.002204309,0.00531041],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08796314,"threshold_uncertainty_score":0.294266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05314749031027283,"score_gpt":0.3212984308924406,"score_spread":0.2681509405821678,"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."}}