{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005170752,0.0002497873,0.0005557717,0.0005709378,0.003641409,0.00007056996,0.0003298496,0.0002504936,0.0002849515],"category_scores_gemma":[0.00009920502,0.000229828,0.0001175627,0.0004027851,0.0001004925,0.0001751648,0.00001985992,0.001022814,0.000431263],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.008693774,"about_ca_system_score_gemma":0.009313717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8288365,"about_ca_topic_score_gemma":0.9672226,"domain_scores_codex":[0.9931899,0.002969325,0.0008858042,0.0005982665,0.0005166933,0.001839999],"domain_scores_gemma":[0.994365,0.003857852,0.0002455049,0.0005588369,0.0002927315,0.0006801069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001710261,0.00009982584,0.02492948,0.000249994,0.00003506765,0.00001850763,0.007185448,0.000001005558,0.00001668233,0.09912908,0.8414096,0.02675433],"study_design_scores_gemma":[0.00509545,0.00229803,0.1638619,0.0004586435,0.00001668817,0.000001005504,0.0238992,0.00006465925,0.00001068502,0.05226025,0.7514466,0.0005868518],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1652364,0.003788428,0.03703882,0.4657308,0.01501734,0.01931254,0.006938453,0.001139787,0.2857975],"genre_scores_gemma":[0.9765347,0.000007467435,0.0002683878,0.0174532,0.001298259,0.000362979,0.000577267,0.00006664154,0.003431135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8112983,"threshold_uncertainty_score":0.9976557,"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."}}