{"id":"W4387603551","doi":"10.3389/jpps.2023.11877","title":"Data collection within patient support programs in Canada and implications for real-world evidence generation: the authors’ perspective","year":2023,"lang":"en","type":"article","venue":"Journal of Pharmacy & Pharmaceutical Sciences","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Gilead Sciences; AstraZeneca; EMD Serono; Alexion Pharmaceuticals; Pfizer","keywords":"Data collection; Data quality; Checklist; Beneficiary; Health care; Data governance; Quality (philosophy); Data science; Perspective (graphical); Computer science; Knowledge management; Medicine; Business; Psychology; Marketing; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3027251,0.0009904423,0.002079082,0.0077786,0.01541694,0.03822763,0.007218838,0.009338484,0.003438012],"category_scores_gemma":[0.5793192,0.001170026,0.002106802,0.01982235,0.03327397,0.01184387,0.01615055,0.01699882,0.0004565848],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2001678,"about_ca_system_score_gemma":0.6624606,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9252771,"about_ca_topic_score_gemma":0.938298,"domain_scores_codex":[0.5974065,0.237412,0.03599712,0.0127196,0.0995417,0.01692302],"domain_scores_gemma":[0.2025491,0.4966642,0.03156199,0.01937762,0.2179659,0.0318812],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005135483,0.000242652,0.04955639,0.01667505,0.0009709003,0.001493668,0.04707109,0.004447355,0.0004310325,0.2663162,0.3031456,0.3091365],"study_design_scores_gemma":[0.0003387668,0.0004538312,0.03349334,0.07276068,0.0008400115,0.0009329483,0.06346638,0.003398039,0.0008766035,0.1078337,0.7149198,0.0006858639],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004842388,0.02456489,0.003745614,0.9523922,0.002911356,0.0004795205,0.000823373,0.00004375856,0.0101969],"genre_scores_gemma":[0.267561,0.08419272,0.05870305,0.5729721,0.00855982,0.00198418,0.00118219,0.0002139477,0.004630967],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.7998322,"threshold_uncertainty_score":0.9276921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8113609547256627,"score_gpt":0.5746252655353494,"score_spread":0.2367356891903133,"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."}}