{"id":"W4389447590","doi":"10.1212/wnl.94.15_supplement.1915","title":"Clinical, Biological, Imaging and Genetic Repository C-BIGR; An Integrated Approach to Biobanking in the Context of Open Science (1915)","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Biobank; Context (archaeology); Open science; Engineering ethics; Knowledge management; Medicine; Engineering; Computer science; Bioinformatics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.1136735,0.001653081,0.002890619,0.01645171,0.004288403,0.01524661,0.009701048,0.004177068,0.02141257],"category_scores_gemma":[0.1688345,0.001794882,0.001871311,0.0175863,0.004170827,0.01205585,0.025579,0.005961074,0.01697602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006333635,"about_ca_system_score_gemma":0.03583462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02765787,"about_ca_topic_score_gemma":0.02517046,"domain_scores_codex":[0.9574897,0.01913204,0.00488966,0.005761279,0.01013334,0.002593941],"domain_scores_gemma":[0.7376083,0.06280106,0.01726976,0.1054749,0.03993241,0.03691356],"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":[0.002611408,0.0002444596,0.01255258,0.0009596086,0.0004363058,0.0007674762,0.002057847,0.003305877,0.003169563,0.107904,0.6833015,0.1826895],"study_design_scores_gemma":[0.000784097,0.0002357149,0.01587627,0.001251754,0.0002227889,0.0009561909,0.0008860309,0.01567913,0.006342047,0.1243058,0.8328558,0.0006045148],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01486787,0.004674532,0.5156181,0.0596834,0.003442391,0.006357252,0.2410431,0.08313167,0.07118164],"genre_scores_gemma":[0.05811819,0.001575539,0.6487191,0.009591652,0.001982652,0.004340656,0.2490287,0.01264875,0.01399489],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9902989,"threshold_uncertainty_score":0.6011699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0666045368260886,"score_gpt":0.3493495365291361,"score_spread":0.2827449997030476,"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."}}