{"id":"W1510720609","doi":"10.1007/978-0-387-48438-9_14","title":"Ontology Design for Biomedical Text Mining","year":2007,"lang":"en","type":"book-chapter","venue":"Semantic Web","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Ontology; Computer science; Information retrieval; Data science; World Wide Web; Epistemology; Philosophy","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0005713993,0.000408969,0.0005273377,0.0001671678,0.0001020846,0.00001819984,0.0003829988,0.001649516,0.0001520544],"category_scores_gemma":[0.0003551241,0.0003630494,0.0002690979,0.00002887409,0.0006235211,9.871994e-7,0.0001461072,0.0002430342,0.00007527482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002334183,"about_ca_system_score_gemma":0.0002917759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003716822,"about_ca_topic_score_gemma":0.00003712294,"domain_scores_codex":[0.9980146,0.00002757351,0.0004649618,0.000702393,0.0002409043,0.0005495182],"domain_scores_gemma":[0.9988332,0.0002023658,0.0002026304,0.0004697029,0.00009807635,0.0001940097],"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":[0.0008822268,0.0001785086,0.00005060743,0.0004672124,0.001224189,0.0002594452,0.0001615911,0.000003676577,0.03343154,0.01293119,0.5031618,0.4472479],"study_design_scores_gemma":[0.0007938053,0.001107508,0.000009937175,0.0001647421,0.0001290789,0.0001063822,0.00003517171,0.0001378676,0.001032781,0.001547661,0.9944432,0.0004918901],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002504861,0.02001514,0.4425197,0.00291695,0.005227465,0.002324422,0.0003626097,0.0003853876,0.5237435],"genre_scores_gemma":[0.02642127,0.001187418,0.1108053,0.002207421,0.00420457,0.00008902857,0.00134953,0.0003118014,0.8534236],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4912813,"threshold_uncertainty_score":0.9998822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05595275854141806,"score_gpt":0.3026791480636952,"score_spread":0.2467263895222771,"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."}}