{"id":"W2297036333","doi":"10.1126/science.351.6271.329","title":"Montreal institute going ‘open’ to accelerate science","year":2016,"lang":"en","type":"article","venue":"Science","topic":"Science, Research, and Medicine","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Open science; Open data; Library science; Political science; Data science; Psychology; Neuroscience; Computer science; World Wide Web; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003817986,0.0001223403,0.0002026391,0.0006601481,0.0007545343,0.0002473497,0.001951767,0.00002346128,0.0001375695],"category_scores_gemma":[0.002677591,0.00006608608,0.00002519419,0.00457634,0.005298549,0.002030158,0.0008576694,0.0001062479,0.0006384419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003094717,"about_ca_system_score_gemma":0.003554224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000298176,"about_ca_topic_score_gemma":0.0001501183,"domain_scores_codex":[0.9960384,0.00001127257,0.000201492,0.0008420883,0.001899193,0.001007562],"domain_scores_gemma":[0.9973862,0.00004708478,0.00004326969,0.0006870991,0.0005555988,0.001280708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005648367,0.00004480641,0.007823667,0.000006515953,0.000001238297,0.00004986179,0.0004864944,0.000001355926,0.8266812,0.001356964,0.0008613746,0.16263],"study_design_scores_gemma":[0.002603963,0.001016271,0.6129865,0.0006878987,0.00001393015,0.0001886792,0.0004002255,0.0003679445,0.3263866,0.0007313582,0.05426713,0.0003494866],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9011312,0.00004296353,0.0009381277,0.00993305,0.0008149617,0.0005693377,0.000002221351,0.00005940607,0.08650871],"genre_scores_gemma":[0.9871165,0.00004128334,0.001837582,0.002431769,0.0001706784,0.00002100578,1.878953e-7,0.000006077714,0.008374962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6051629,"threshold_uncertainty_score":0.9974084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08658621409028214,"score_gpt":0.4279518623894133,"score_spread":0.3413656482991312,"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."}}