{"id":"W1555519040","doi":"10.3233/sw-2011-0048","title":"Taking flight with OWL2","year":2011,"lang":"en","type":"article","venue":"Semantic Web","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Aeronautics; Computer science; Engineering","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":[0.00008076687,0.00009364392,0.00009251436,0.00002241511,0.00004641738,0.000007446293,0.0001397635,0.0001013749,0.0001198139],"category_scores_gemma":[0.00004719153,0.00006451276,0.00003288476,0.00005785159,0.0001325458,9.712694e-7,0.00005343101,0.00005744725,0.00004215924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002557268,"about_ca_system_score_gemma":0.00004033403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002377315,"about_ca_topic_score_gemma":0.00005334845,"domain_scores_codex":[0.999411,0.00001846734,0.00008820552,0.0002072189,0.00008116904,0.0001939555],"domain_scores_gemma":[0.9996385,0.000004861265,0.00005089243,0.0002261051,0.00002522036,0.00005442722],"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":[0.0006702782,0.0005287679,0.1117048,0.0001670296,0.0005856928,0.0003246417,0.001791483,0.000003689384,0.6759588,0.002320165,0.02537118,0.1805735],"study_design_scores_gemma":[0.003014268,0.003150294,0.09231637,0.0002790209,0.0001674745,0.0004139348,0.001245845,0.0003212226,0.5622103,0.0005631391,0.334975,0.00134313],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572956,0.0005494031,0.002917432,0.0001581645,0.0001651927,0.00006797857,0.00000272572,0.00004961873,0.03879391],"genre_scores_gemma":[0.9943451,0.00003444824,0.004248838,0.0002011264,0.0001137039,0.000005617312,0.000009210296,0.00001220522,0.00102976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3096039,"threshold_uncertainty_score":0.2630754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02682263809042286,"score_gpt":0.2404968067435917,"score_spread":0.2136741686531688,"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."}}