{"id":"W4296091000","doi":"10.25071/1708-6701.40422","title":"CAML members reflect (1)","year":2021,"lang":"en","type":"article","venue":"CAML Review / Revue de l ACBM","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computational biology; Natural language processing; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01351204,0.00119579,0.0008928155,0.003164826,0.003019331,0.01215746,0.002556203,0.007226011,0.3874801],"category_scores_gemma":[0.06372205,0.0005682454,0.0008527251,0.002897124,0.001769728,0.006781804,0.007154624,0.006157046,0.3642734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005620095,"about_ca_system_score_gemma":0.0149843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01148933,"about_ca_topic_score_gemma":0.02833848,"domain_scores_codex":[0.9889352,0.002192145,0.0004011616,0.001227134,0.006144441,0.001099923],"domain_scores_gemma":[0.9426916,0.007014807,0.002856051,0.003838196,0.02781437,0.01578494],"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":[0.000009763003,0.000004106304,0.00005751749,0.00002744986,8.97325e-7,0.00000688573,0.0000231972,0.000003075445,0.00003836866,0.001512209,0.9865449,0.01177168],"study_design_scores_gemma":[0.000003333291,0.000002752459,0.00007856524,0.00005283849,0.000001623729,0.00001165173,0.00003906502,0.00001193035,0.00003394743,0.0004395339,0.9993221,0.00000265836],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0005077305,0.007094938,0.003319426,0.5176294,0.1048663,0.0002414138,0.005751248,0.002755384,0.3578342],"genre_scores_gemma":[0.0045583,0.005172279,0.005340553,0.08813649,0.01906537,0.0005206022,0.005745566,0.00170087,0.8697599],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3874801,"threshold_uncertainty_score":0.8736853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02174173544848011,"score_gpt":0.315036077124119,"score_spread":0.2932943416756388,"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."}}