{"id":"W4298068589","doi":"10.5281/zenodo.7126988","title":"Legacy Submission","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Carleton University; Simon Fraser University","funders":"","keywords":"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005636403,0.001727109,0.002287108,0.005580867,0.002125133,0.01040585,0.004097488,0.002534142,0.8624583],"category_scores_gemma":[0.04480858,0.001058127,0.001741114,0.008725326,0.0007290887,0.005068193,0.005845647,0.00263872,0.7977585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002014459,"about_ca_system_score_gemma":0.005994412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004023376,"about_ca_topic_score_gemma":0.005346407,"domain_scores_codex":[0.9956223,0.0006407355,0.000735196,0.001105092,0.001429822,0.0004668206],"domain_scores_gemma":[0.9729585,0.005722177,0.0009705918,0.006452246,0.01177942,0.002117096],"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":[0.00008596263,0.00001385297,0.0001837018,0.0002858717,0.00001170895,0.00001970184,0.00002374255,0.00003159862,0.00006214473,0.0007561639,0.9872562,0.01126934],"study_design_scores_gemma":[0.00008648634,0.00001683438,0.0006187683,0.0002249987,0.00001089997,0.00003117261,0.00007690486,0.00007974009,0.0001772,0.002284421,0.9963722,0.00002029828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003068183,0.0001950778,0.002384709,0.001958433,0.002968121,0.0004041039,0.925459,0.01248899,0.05383477],"genre_scores_gemma":[0.003071534,0.0005760168,0.006525128,0.002180055,0.0009269138,0.002046551,0.8450186,0.01407698,0.1255782],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1375417,"threshold_uncertainty_score":0.1961864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02023038370000991,"score_gpt":0.2420169629581332,"score_spread":0.2217865792581233,"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."}}