{"id":"W1983622849","doi":"10.1038/nbt1203-1433","title":"Time to drop the language of 'consensus'","year":2003,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Science, Research, and Medicine","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal General Hospital","funders":"","keywords":"Drop (telecommunication); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004769239,0.00008184735,0.0002037915,0.0002569342,0.00004108388,0.000001949346,0.0002092406,0.0005469499,0.0004343592],"category_scores_gemma":[0.00222572,0.00004526938,0.00004268023,0.0008068944,0.0005237487,0.000006183119,0.00004473467,0.000790671,0.0002344216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002685411,"about_ca_system_score_gemma":0.0001201124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001527039,"about_ca_topic_score_gemma":0.000007698583,"domain_scores_codex":[0.999083,0.00003328202,0.0001284017,0.0002066003,0.0002788957,0.0002698228],"domain_scores_gemma":[0.999177,0.00009216864,0.00003334841,0.0005204221,0.00008583939,0.00009118306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006898493,0.00007413395,0.0003069627,0.00002552284,0.00003053695,0.0001075012,0.0004397894,2.876047e-7,0.9434102,0.008440086,0.02850214,0.01859382],"study_design_scores_gemma":[0.0007987221,0.0005776512,0.001509907,0.00005188272,0.00003049502,0.000400113,0.001507612,0.00002944772,0.6379834,0.0001365597,0.3568927,0.00008150371],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9207955,0.003016364,0.00002662068,0.0553246,0.0001800671,0.0004442162,0.00000484,0.0001091303,0.02009864],"genre_scores_gemma":[0.9852609,0.00003425157,0.000887525,0.002806823,0.00006292237,0.000005787453,0.000001898645,0.000009161951,0.01093073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3283906,"threshold_uncertainty_score":0.4755929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006901942545911138,"score_gpt":0.3065726039998831,"score_spread":0.2996706614539719,"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."}}