{"id":"W2509885322","doi":"10.1093/database/baw121","title":"BioCreative V BioC track overview: collaborative biocurator assistant task for BioGRID","year":2016,"lang":"en","type":"article","venue":"Database","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute; Université de Montréal; Institute for Research in Immunology and Cancer","funders":"National Institute of General Medical Sciences; Biotechnology and Biological Sciences Research Council; National Institutes of Health","keywords":"Computer science; Usability; Annotation; Task (project management); Interoperability; Classifier (UML); World Wide Web; Information retrieval; Data curation; Crowdsourcing; Natural language processing; Artificial intelligence; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0170595,0.002735619,0.002083882,0.004400817,0.003352303,0.005351027,0.005879368,0.002701758,0.02687118],"category_scores_gemma":[0.01977303,0.001688754,0.002026909,0.005271286,0.0005717172,0.005621374,0.006499064,0.002248186,0.03523684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002791755,"about_ca_system_score_gemma":0.007993827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03251192,"about_ca_topic_score_gemma":0.03103391,"domain_scores_codex":[0.9935921,0.001512626,0.0007220195,0.001555908,0.001904915,0.0007124021],"domain_scores_gemma":[0.9805921,0.00399999,0.001167162,0.006180745,0.005391428,0.002668542],"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":[0.001246498,0.0004902922,0.004354779,0.001057776,0.0001821951,0.0002166773,0.001005138,0.001759372,0.01096067,0.00211654,0.878077,0.09853312],"study_design_scores_gemma":[0.000998131,0.0008226304,0.0124191,0.0002484935,0.000171401,0.0005523171,0.0007160143,0.02359476,0.02729646,0.00377033,0.9291117,0.0002987442],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.03582902,0.002597782,0.3038677,0.003486394,0.001464328,0.006897336,0.2477119,0.3544305,0.04371513],"genre_scores_gemma":[0.03965177,0.0006808827,0.2936366,0.0009860748,0.0002960482,0.005909239,0.5991034,0.03035622,0.02937982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03251192,"threshold_uncertainty_score":0.09022039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02559781275306474,"score_gpt":0.3119697022994703,"score_spread":0.2863718895464056,"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."}}