{"id":"W2809969667","doi":"10.29173/iq753","title":"Providing Context for Understanding: Insight from Research on Two Canadian Health Surveys","year":2006,"lang":"en","type":"article","venue":"IASSIST Quarterly","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Data science; Management science; Computer science; Geography; Engineering; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1050136,0.001039745,0.002132278,0.01221308,0.02056067,0.01814254,0.006242436,0.003964207,0.002622319],"category_scores_gemma":[0.2536817,0.001550168,0.001317128,0.02631159,0.02204539,0.01695162,0.01655846,0.004925039,0.0001893858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07899296,"about_ca_system_score_gemma":0.1352004,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.92748,"about_ca_topic_score_gemma":0.9570143,"domain_scores_codex":[0.8891432,0.06642844,0.005264648,0.005347694,0.02420751,0.009608603],"domain_scores_gemma":[0.6508746,0.2629004,0.01964041,0.01581811,0.04659778,0.004168732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00005369916,0.00003278569,0.02771985,0.001067946,0.0001160553,0.0004896245,0.8965611,0.0001584479,0.000348833,0.03319366,0.006303729,0.03395423],"study_design_scores_gemma":[0.00002303137,0.00002400499,0.06977976,0.003481455,0.0002276188,0.0002372237,0.8511477,0.0002570816,0.0004031284,0.01487901,0.05942113,0.0001189417],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6239374,0.05040966,0.03146078,0.166493,0.0007432215,0.00113514,0.004742524,0.00007584019,0.1210026],"genre_scores_gemma":[0.971808,0.007394104,0.0108446,0.007016555,0.00007582353,0.00057023,0.0007310623,0.00007228366,0.00148722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.92748,"threshold_uncertainty_score":0.5731367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3649748874204179,"score_gpt":0.512212906353821,"score_spread":0.1472380189334031,"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."}}