{"id":"W3122931688","doi":"10.1038/npre.2009.3231.1","title":"Developing ontologies in decentralised settings","year":2009,"lang":"en","type":"preprint","venue":"Nature Precedings","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Terry Fox Research Institute","funders":"","keywords":"Ontology; Computer science; Context (archaeology); IDEF5; Best practice; Knowledge management; Ontology engineering; Data science; Point (geometry); Foundation (evidence); Management science; Process management; Process ontology; Engineering; Political science; Domain knowledge","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":[0.02690056,0.000364927,0.000814087,0.002701735,0.002746984,0.005556924,0.002648647,0.001978742,0.002359635],"category_scores_gemma":[0.03076747,0.0007719877,0.001010268,0.001768598,0.007002137,0.0134098,0.01122496,0.002978217,0.0006266736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002921978,"about_ca_system_score_gemma":0.003905308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001968276,"about_ca_topic_score_gemma":0.002726696,"domain_scores_codex":[0.9713201,0.01891148,0.001721464,0.00332613,0.004121658,0.0005991363],"domain_scores_gemma":[0.9591722,0.01867576,0.003275104,0.01373904,0.003839109,0.001298773],"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":[0.00009294166,0.0003521416,0.005130175,0.0005275773,0.0001437559,0.0006536728,0.02032465,0.04042064,0.009349753,0.7617926,0.00218124,0.1590308],"study_design_scores_gemma":[0.00008162949,0.0001704082,0.002027654,0.0005005541,0.00005899997,0.0005424766,0.007294427,0.1427033,0.01296078,0.7560577,0.07751532,0.00008676082],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0445156,0.0001737901,0.9450021,0.001200294,0.00003324842,0.0003078302,0.00003533444,0.0004886285,0.008243088],"genre_scores_gemma":[0.3371992,0.0001505496,0.6589426,0.0001794715,0.00002029325,0.0003181337,0.0000975395,0.0001442361,0.002948022],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02690056,"threshold_uncertainty_score":0.1422654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02121168142612652,"score_gpt":0.3034751032599575,"score_spread":0.282263421833831,"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."}}