{"id":"W2913956427","doi":"10.1371/journal.pbio.3000120","title":"Open notebook science can maximize impact for rare disease projects","year":2019,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; University of Toronto","funders":"Novartis Pharma; Fundação de Amparo à Pesquisa do Estado de São Paulo; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Huntington Society of Canada; Ontario Genomics; Genome Canada; Ontario Ministry of Research, Innovation and Science; CHDI Foundation; Pfizer","keywords":"Open science; Transparency (behavior); Publication; Open data; Public domain; Biology; Open research; Process (computing); Data science; Domain (mathematical analysis); Open source; Computer science; World Wide Web; Software; Business; Operating system","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":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.07686492,0.001476302,0.001075422,0.006691751,0.006114833,0.02807387,0.006041517,0.00666626,0.1848314],"category_scores_gemma":[0.2330314,0.00151102,0.002227011,0.005489652,0.007123337,0.03062388,0.03949546,0.01144629,0.08297809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003750393,"about_ca_system_score_gemma":0.01364178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008307445,"about_ca_topic_score_gemma":0.001505913,"domain_scores_codex":[0.9626558,0.01783027,0.001900814,0.003337438,0.01206813,0.002207519],"domain_scores_gemma":[0.6389259,0.2093396,0.01164276,0.0724474,0.02556634,0.04207815],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000328037,0.0001719458,0.0008877566,0.0005648118,0.00004086968,0.0003658648,0.002822116,0.0008666056,0.001896887,0.1964073,0.5846245,0.2110233],"study_design_scores_gemma":[0.00009295952,0.00005723319,0.0004204953,0.0002609898,0.00001256604,0.000125305,0.0004007822,0.0004406511,0.001007468,0.08492583,0.9121902,0.00006547458],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006982365,0.003175342,0.3605933,0.1265721,0.02267298,0.001464728,0.00769385,0.05240777,0.4184375],"genre_scores_gemma":[0.1093551,0.008271919,0.4503376,0.03866109,0.02360039,0.008238111,0.01496991,0.04987681,0.296689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9939585,"threshold_uncertainty_score":0.6183227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0237900360340822,"score_gpt":0.3063510204906908,"score_spread":0.2825609844566086,"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."}}