{"id":"W2463732179","doi":"","title":"[Searching for and processing professional and scientific data 2/2].","year":2011,"lang":"en","type":"article","venue":"PubMed","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Obsolescence; Computer science; Value (mathematics); Subject (documents); Data science; Knowledge management; Sociology of scientific knowledge; Business; World Wide Web; Machine learning; Sociology; Marketing","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":[0.0004819525,0.00004845734,0.00005136112,0.0000208143,0.0001497694,0.00003769942,0.0001413685,0.00005764685,8.617795e-7],"category_scores_gemma":[0.0002607671,0.0000368398,0.000006817855,0.00002791132,0.0002759309,0.000004370053,0.0002912089,0.0000377855,1.369697e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001217062,"about_ca_system_score_gemma":0.00002737701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003206176,"about_ca_topic_score_gemma":0.000007803524,"domain_scores_codex":[0.9993971,0.00001500289,0.00006455355,0.0002908472,0.00005425673,0.0001782414],"domain_scores_gemma":[0.9997053,0.00001111235,0.00002351655,0.0001672891,0.00002157969,0.00007126813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00004311671,0.0000218857,0.002836594,0.0000497656,0.000008413753,4.32131e-7,0.0001143324,5.54391e-9,0.002205709,0.00007742958,0.001450771,0.9931915],"study_design_scores_gemma":[0.001611789,0.0001652076,0.6283,0.00005319092,0.000047833,0.00004926719,0.0005209941,0.0005782752,0.0179319,0.004630018,0.3456493,0.0004622798],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991431,0.004479823,0.00242687,0.0003209699,0.0002624053,0.0004238978,0.00004488391,0.00002031313,0.0005898451],"genre_scores_gemma":[0.9900666,0.00001872854,0.008422558,0.00005155664,0.00007755566,0.0001693368,0.00008416076,0.000005970236,0.001103523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9927292,"threshold_uncertainty_score":0.1502284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1604917323909491,"score_gpt":0.3164719878232611,"score_spread":0.1559802554323119,"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."}}