{"id":"W4313437327","doi":"10.1002/ajmg.c.32028","title":"Data sharing to advance gene‐targeted therapies in rare diseases","year":2023,"lang":"en","type":"article","venue":"American Journal of Medical Genetics Part C Seminars in Medical Genetics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Data sharing; Harmonization; Translational research; Globe; Standardization; Medicine; Data science; Ethical issues; Scale (ratio); Computer science; Engineering ethics; Alternative medicine; Engineering; Geography; Pathology","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":["metaresearch"],"category_scores_codex":[0.2671944,0.001269621,0.002104173,0.00709314,0.004612614,0.01541658,0.008930849,0.007991093,0.02283126],"category_scores_gemma":[0.3404828,0.001673694,0.003659972,0.007809886,0.01032603,0.04030001,0.03652098,0.0146823,0.007583203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006921059,"about_ca_system_score_gemma":0.04069096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002427684,"about_ca_topic_score_gemma":0.002030063,"domain_scores_codex":[0.8177426,0.1373762,0.01334909,0.007709752,0.01979348,0.004028992],"domain_scores_gemma":[0.4948899,0.2659277,0.01891346,0.14299,0.04623358,0.03104521],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000480471,0.0002066958,0.003136381,0.001440047,0.0003658149,0.0005087939,0.004823885,0.003926982,0.001698536,0.539087,0.1860127,0.2583127],"study_design_scores_gemma":[0.0001265577,0.0001345766,0.0007875417,0.00185675,0.00008200746,0.0004220628,0.00181806,0.00255764,0.001292944,0.4061851,0.5846129,0.0001239921],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003847835,0.007684635,0.4841258,0.4290237,0.008384825,0.001359968,0.001769359,0.003410384,0.06039356],"genre_scores_gemma":[0.1184963,0.01683611,0.7317215,0.09365219,0.01147796,0.003632882,0.006069725,0.002752792,0.0153604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9910691,"threshold_uncertainty_score":0.9036798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660401030378926,"score_gpt":0.3594041883646288,"score_spread":0.3428001780608395,"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."}}