{"id":"W6967466544","doi":"10.5281/zenodo.1158769","title":"Open Lab Notebooks: An Extreme Open Science Initiative - Open Notebooker Presentations - Project Introductions","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Novartis Pharma; University of Toronto; Ontario Ministry of Research, Innovation and Science; Fundação de Amparo à Pesquisa do Estado de São Paulo; University of Oxford; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Genome Canada; Ontario Genomics; Pfizer","keywords":"Open science; Open source; Open university; Open data; Citizen science; Open research","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004055772,0.001730556,0.001076443,0.002517365,0.002535599,0.01022055,0.003190329,0.002184039,0.700128],"category_scores_gemma":[0.01088124,0.0008631804,0.0009989837,0.002388614,0.0007724065,0.00683806,0.008861111,0.003880193,0.533419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001748847,"about_ca_system_score_gemma":0.003177003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001674678,"about_ca_topic_score_gemma":0.00411345,"domain_scores_codex":[0.9975792,0.0003210586,0.00008296652,0.0002821544,0.001407745,0.0003269071],"domain_scores_gemma":[0.9877841,0.001921543,0.0003079543,0.001330191,0.003222233,0.00543406],"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":[0.00003836114,0.00003202487,0.00001566726,0.00004771763,8.753628e-7,0.00002141339,0.00007488332,0.00003638821,0.0003336553,0.001428717,0.977563,0.02040725],"study_design_scores_gemma":[0.00001760224,0.00001670233,0.000120445,0.00003582595,9.953153e-7,0.00002050454,0.00009190013,0.00005491016,0.0001987735,0.001246921,0.9981834,0.0000120367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002291077,0.001379988,0.04288037,0.008796222,0.02454927,0.002671013,0.03679381,0.07352797,0.8071102],"genre_scores_gemma":[0.002908625,0.0006526317,0.01379187,0.001090038,0.003085892,0.0009775285,0.01449513,0.01351024,0.9494881],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9968097,"threshold_uncertainty_score":0.427731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1218910520600615,"score_gpt":0.3569039814531351,"score_spread":0.2350129293930735,"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."}}