{"id":"W131909739","doi":"10.17705/1jais.00332","title":"Extending Classification Principles from Information Modeling to Other Disciplines","year":2013,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Memorial University of Newfoundland","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Inference; Class (philosophy); Context (archaeology); Data science; Domain (mathematical analysis); Information system; Information processing; Artificial intelligence; Information theory; Cognition; Management science; Theoretical computer science; Cognitive science; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01282617,0.001293735,0.001645867,0.008268844,0.002921417,0.009683217,0.00338689,0.003241072,0.004335759],"category_scores_gemma":[0.01504331,0.000976195,0.003625907,0.007970538,0.01392364,0.0211151,0.006181166,0.006011061,0.001090978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006788453,"about_ca_system_score_gemma":0.004295872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007512102,"about_ca_topic_score_gemma":0.005026105,"domain_scores_codex":[0.9908535,0.003512718,0.001042013,0.00130676,0.002840912,0.0004440798],"domain_scores_gemma":[0.9855678,0.008460499,0.0008163792,0.003005451,0.001722103,0.0004277201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003516678,0.00001183986,0.0001691886,0.00006257136,0.00002060272,0.00002826845,0.0002823723,0.002490285,0.00007761716,0.9837731,0.001119639,0.01196103],"study_design_scores_gemma":[0.000005426282,0.000005410862,0.00008665227,0.00005001135,0.00001130393,0.00003147464,0.00005506566,0.008593875,0.0001294081,0.9744678,0.01655354,0.000009963836],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002767449,0.001694879,0.965333,0.009875756,0.000236386,0.0001553762,0.0001914289,0.0002733859,0.01947241],"genre_scores_gemma":[0.2088818,0.00449263,0.7749168,0.003075409,0.001168586,0.0009397264,0.0006896377,0.00025746,0.005578086],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01282617,"threshold_uncertainty_score":0.06783211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04301503069581954,"score_gpt":0.26359752972576,"score_spread":0.2205824990299405,"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."}}