{"id":"W7069208697","doi":"","title":"Only a ban will do","year":2016,"lang":"en","type":"article","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Risk assessment; Government (linguistics); Human health","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":[0.004323614,0.0009355855,0.001187161,0.001600187,0.005371531,0.009942214,0.001928826,0.00611694,0.547637],"category_scores_gemma":[0.01158731,0.000618329,0.001000623,0.000962949,0.004088676,0.007360029,0.009909945,0.006711377,0.5702417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001457006,"about_ca_system_score_gemma":0.003659692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0044138,"about_ca_topic_score_gemma":0.01129114,"domain_scores_codex":[0.9966888,0.000533097,0.0001136525,0.000639823,0.001255471,0.00076911],"domain_scores_gemma":[0.9888953,0.0008743768,0.000319933,0.002450523,0.002225552,0.005234251],"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":[0.00007102566,0.00003728773,0.0002591433,0.00006538649,0.00000592948,0.00005065061,0.0002177995,0.00001605877,0.0004580363,0.02914181,0.9395421,0.03013474],"study_design_scores_gemma":[0.000006901501,0.000009710953,0.000236075,0.00002325805,0.000002170209,0.00002165599,0.0001194185,0.00001043608,0.0000596255,0.002170976,0.9973317,0.000007992928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001418081,0.001638698,0.002546096,0.08902638,0.0392061,0.0001171311,0.001051716,0.001569721,0.8634261],"genre_scores_gemma":[0.002793304,0.0002666481,0.0004425309,0.01164272,0.001979505,0.00004413109,0.0002738559,0.0004021449,0.9821551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.547637,"threshold_uncertainty_score":0.6452409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01352050903269927,"score_gpt":0.2538871470880418,"score_spread":0.2403666380553426,"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."}}