{"id":"W4310088355","doi":"10.5281/zenodo.7369365","title":"[A^I^R™]** TEXANS vs DOLPHINS LIVE FREE","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004961605,0.001221954,0.0008821506,0.001976147,0.0007993818,0.002166506,0.001204388,0.0007513429,0.1669339],"category_scores_gemma":[0.004220371,0.0003336905,0.0008971397,0.0026938,0.0003182816,0.002126003,0.00148297,0.001475573,0.1364896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008168268,"about_ca_system_score_gemma":0.0006312672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0329261,"about_ca_topic_score_gemma":0.05310405,"domain_scores_codex":[0.9992513,0.00008826378,0.00006106889,0.000279092,0.0001713948,0.0001487682],"domain_scores_gemma":[0.9985846,0.0003442934,0.0001402504,0.0003419511,0.0004448435,0.0001440984],"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":[0.0001132385,0.00001691073,0.001712834,0.0001988375,0.00001568761,0.000009679562,0.00002829326,0.00006876617,0.0001196741,0.0003552353,0.9924226,0.00493834],"study_design_scores_gemma":[0.000147941,0.00005131825,0.01972419,0.0002084515,0.00001886419,0.00006553264,0.0003594627,0.0004227266,0.0004080118,0.0008933522,0.9776684,0.00003171812],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002572219,0.0002089643,0.0002124747,0.0003712151,0.000654755,0.00003873454,0.981642,0.002212177,0.01208743],"genre_scores_gemma":[0.006132866,0.0001567263,0.000668895,0.0002989641,0.00008236148,0.0001036868,0.9793514,0.0007941185,0.01241112],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.833066,"threshold_uncertainty_score":0.5584496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02876050108202931,"score_gpt":0.2510208505583492,"score_spread":0.2222603494763199,"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."}}