{"id":"W4310599199","doi":"10.1093/femsyr/foac061","title":"Industry and academia—a perfect match","year":2022,"lang":"en","type":"article","venue":"FEMS Yeast Research","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0009747007,0.00006021811,0.0001178449,0.0002209196,0.0004010309,0.000008164667,0.0001232344,0.004635245,0.001714343],"category_scores_gemma":[0.00009423308,0.00005094379,0.00002442617,0.0004903988,0.0002522804,0.00002074191,0.0004094487,0.03993881,0.00009606864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005835788,"about_ca_system_score_gemma":0.0001150739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005313689,"about_ca_topic_score_gemma":0.000001016718,"domain_scores_codex":[0.9988375,0.0001238569,0.00009165622,0.0002154002,0.0004030685,0.0003285054],"domain_scores_gemma":[0.9995803,0.00004930399,0.00001243243,0.000206748,0.00003960581,0.0001116221],"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":[0.001783592,0.0009529039,0.21617,0.0004407948,0.0005374048,0.002266809,0.003782276,0.00002241729,0.125333,0.02676457,0.4672033,0.154743],"study_design_scores_gemma":[0.002326722,0.001253555,0.08882493,0.00009424884,0.00004043342,0.002666425,0.004973844,0.0006074723,0.00915786,0.001235664,0.8885723,0.0002465996],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9073948,0.0012242,0.000003068408,0.07712,0.00008857737,0.0002233054,0.000005525059,0.00006769702,0.0138728],"genre_scores_gemma":[0.9802523,0.0002233293,0.00002800772,0.000495048,0.00009267091,0.00004511348,0.000006704162,0.00001246471,0.01884435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.421369,"threshold_uncertainty_score":0.9991982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0634592255425602,"score_gpt":0.378401959219382,"score_spread":0.3149427336768218,"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."}}