{"id":"W6950236642","doi":"10.5683/sp2/qhkyfl","title":"Data from: Mandated data archiving greatly improves access to research data","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Data access; Population; Data Protection Act 1998; Genetic data; Inclusion (mineral); Odds; Data sharing; Control (management)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.03701489,0.001400419,0.001626397,0.008675194,0.002618779,0.008303719,0.004612157,0.002197979,0.03761958],"category_scores_gemma":[0.189901,0.00103021,0.002308993,0.01291961,0.001620761,0.00434897,0.006568946,0.002699609,0.02694465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003873587,"about_ca_system_score_gemma":0.01250087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02075661,"about_ca_topic_score_gemma":0.0550334,"domain_scores_codex":[0.9584368,0.01319308,0.0111085,0.006118284,0.009334057,0.001809286],"domain_scores_gemma":[0.865962,0.04460478,0.0161594,0.050268,0.01925164,0.00375413],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.002466938,0.0002368869,0.0516196,0.008207801,0.0007730351,0.0003029337,0.001495028,0.002226214,0.004543672,0.01665759,0.8638475,0.04762284],"study_design_scores_gemma":[0.0006843462,0.0001210467,0.04900546,0.002097261,0.0003779776,0.0004778875,0.0005803043,0.00167266,0.005101659,0.008146044,0.9314883,0.0002472201],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008112302,0.0005530949,0.005775904,0.002085138,0.000414522,0.0004090969,0.9632455,0.004484983,0.01491938],"genre_scores_gemma":[0.02868607,0.0003878092,0.03516652,0.001281035,0.0001220618,0.001648485,0.9268917,0.00209731,0.003719044],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9953879,"threshold_uncertainty_score":0.1957558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4541766521171022,"score_gpt":0.4926262112377123,"score_spread":0.03844955912061004,"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."}}