{"id":"W2965977938","doi":"10.23889/ijpds.v4i1.1106","title":"Notches on the dial: a call to action to develop plain language communication with the public about users and uses of health data","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Focus Groups and Qualitative Methods","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of British Columbia; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Call to action; Action (physics); Dial; Computer science; Plain language; Psychology; Linguistics; Engineering; Business; Advertising","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.1858175,0.001587557,0.002643698,0.003943826,0.02709136,0.02589785,0.01113132,0.05636061,0.03149606],"category_scores_gemma":[0.2436081,0.001993505,0.00231628,0.002275708,0.05211199,0.06698343,0.04576507,0.0862958,0.009432306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01485393,"about_ca_system_score_gemma":0.05681276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01052057,"about_ca_topic_score_gemma":0.01016116,"domain_scores_codex":[0.8161937,0.1395994,0.006172427,0.007347938,0.02353749,0.007149004],"domain_scores_gemma":[0.5379202,0.3504557,0.01302239,0.01983928,0.0345488,0.04421358],"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":[0.000166224,0.0002401246,0.001464905,0.001377191,0.00004572769,0.0008193158,0.2100801,0.00009812053,0.001630162,0.1044369,0.5941298,0.08551154],"study_design_scores_gemma":[0.00005758147,0.0001115794,0.0008019778,0.004718955,0.00002221656,0.0007288591,0.1571751,0.000284002,0.0004364611,0.08746821,0.7480577,0.0001373948],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0009380218,0.001799879,0.003714207,0.9855355,0.004586116,0.00008769153,0.00004634669,0.0001421848,0.003150145],"genre_scores_gemma":[0.03724505,0.003791436,0.01708078,0.9296761,0.003596434,0.0008330045,0.000119635,0.0004063554,0.007251162],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9741021,"threshold_uncertainty_score":0.9827085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3586367229366417,"score_gpt":0.5420807147469173,"score_spread":0.1834439918102756,"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."}}