{"id":"W2039428138","doi":"10.1016/j.socscimed.2006.09.007","title":"Integrating conventional science and aboriginal perspectives on diabetes using fuzzy cognitive maps","year":2006,"lang":"en","type":"article","venue":"Social Science & Medicine","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":109,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mohawk College; Carleton University; Health Canada; University of Ottawa","funders":"","keywords":"Fuzzy cognitive map; Cognition; MEDLINE; Spirituality; Stressor; Perspective (graphical); Diabetes management; Biomedicine; Complexity science; Cognitive map; Psychology; Fuzzy logic; Data science; Computer science; Management science; Medicine; Sociology; Gerontology; Alternative medicine; Fuzzy set; Diabetes mellitus; Artificial intelligence; Clinical psychology; Political science; Bioinformatics; Engineering; Type 2 diabetes; Psychiatry; Pathology","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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.003223085,0.0001897429,0.0002200388,0.0005941534,0.002484006,0.0003584702,0.0008840806,0.00003507334,0.00001468714],"category_scores_gemma":[0.0009156363,0.0001514177,0.00003550848,0.004105355,0.01024102,0.001827439,0.0001780195,0.0002146955,0.000006284085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003345897,"about_ca_system_score_gemma":0.0009710888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001967224,"about_ca_topic_score_gemma":0.00001046114,"domain_scores_codex":[0.9960974,0.00005200712,0.0002426806,0.0009330608,0.001930487,0.0007444007],"domain_scores_gemma":[0.9980996,0.0001859716,0.0001614423,0.0001356635,0.001234245,0.0001830366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000006190515,0.00006083579,0.01025436,0.000008628327,0.000004231279,0.00001034149,0.01519707,0.00000163007,0.09201252,0.8586698,0.000144272,0.02363017],"study_design_scores_gemma":[0.007562263,0.00307412,0.4519997,0.003049943,0.0001666448,0.0001367206,0.1698733,0.05374435,0.04412707,0.2584794,0.004314435,0.003472148],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9265625,0.0001827903,0.02091868,0.002585487,0.0006100147,0.0002607801,0.000005335581,0.0001022557,0.04877211],"genre_scores_gemma":[0.9978439,0.000005514737,0.001083855,0.0004649147,0.0005486871,0.000008281493,0.0000010934,0.000004304525,0.00003947551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6001904,"threshold_uncertainty_score":0.9988146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01821264904801685,"score_gpt":0.323539767162316,"score_spread":0.3053271181142992,"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."}}