{"id":"W2611551016","doi":"10.4018/jdm.2017010101","title":"Thirty Years Later","year":2017,"lang":"en","type":"article","venue":"Journal of Database Management","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Scripting language; Ontology; Conceptual model; Rule-based machine translation; Epistemology; Management science; Artificial intelligence; Programming language; Philosophy; 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":[0.0004993754,0.00005955154,0.0001135745,0.00008714303,0.0001068281,0.0003087863,0.001685852,0.00001322318,0.00001918358],"category_scores_gemma":[0.00003475397,0.0000441144,0.00005837493,0.00002810237,0.00003078025,0.0008941315,0.0008327332,0.00008394741,0.00005459867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001451168,"about_ca_system_score_gemma":0.00001078707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006885174,"about_ca_topic_score_gemma":0.000003297592,"domain_scores_codex":[0.9992836,0.00001870456,0.000189808,0.0001057648,0.0002705686,0.0001315808],"domain_scores_gemma":[0.9987282,0.00001573921,0.0002942302,0.0008768647,0.00003670919,0.00004828347],"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":[0.00005897937,0.0002087749,0.02225423,0.0001721971,0.0006326934,0.01176751,0.0007007323,0.00004152348,0.0005669172,0.2128727,0.2747296,0.4759941],"study_design_scores_gemma":[0.001962269,0.000190722,0.6518158,0.0002586263,0.00009520738,0.0002176185,0.0001898834,0.001751895,0.00133487,0.006718928,0.3351209,0.0003432322],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2883732,0.0007219402,0.6175577,0.01867,0.00747493,0.0003599614,0.00001391687,0.0001177748,0.06671056],"genre_scores_gemma":[0.8311095,0.0003015656,0.1668711,0.0005839154,0.00017826,0.000001091001,8.577879e-7,0.000005252806,0.0009483883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6295616,"threshold_uncertainty_score":0.3132761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043648919459441,"score_gpt":0.2856213410340686,"score_spread":0.2551848518394741,"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."}}