{"id":"W2788150357","doi":"10.12688/mniopenres.12780.1","title":"Defining Success in Open Science","year":2018,"lang":"en","type":"article","venue":"MNI Open Research","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Genome Alberta; Wellcome Trust; Genome Canada; Bill and Melinda Gates Foundation","keywords":"Variety (cybernetics); Construct (python library); Open innovation; Public relations; Process (computing); Political science; Business; Open science; Marketing; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.04251921,0.00008959521,0.0003011599,0.0007162443,0.0006366051,0.0008220524,0.003833655,0.00008312744,0.002070894],"category_scores_gemma":[0.103338,0.00006734882,0.00001526488,0.003647808,0.002007733,0.0007820649,0.005384894,0.001091658,0.001845596],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006188992,"about_ca_system_score_gemma":0.03093421,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01518547,"about_ca_topic_score_gemma":0.001202265,"domain_scores_codex":[0.9935944,0.0003624922,0.0003023451,0.0005998083,0.002613124,0.002527841],"domain_scores_gemma":[0.9893508,0.0008145635,0.00003230697,0.001021668,0.001384713,0.00739595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003728128,0.001137318,0.2483089,0.0003933765,0.00001736556,0.001184375,0.002585899,2.500455e-7,0.008377058,0.0311989,0.2583089,0.4447595],"study_design_scores_gemma":[0.009611023,0.005624244,0.3943279,0.002004525,0.000004198339,0.00009414388,0.001790847,0.001114347,0.02533598,0.002910911,0.5568636,0.0003181987],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4349511,0.0001100502,0.000008852726,0.03485167,0.00008552515,0.002275759,0.000003170885,0.00001079764,0.5277031],"genre_scores_gemma":[0.9872006,0.0000834884,0.001234946,0.004016597,0.0001610102,0.0001541651,0.000005250071,0.00001730517,0.007126591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5522496,"threshold_uncertainty_score":0.9989316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5943257875972783,"score_gpt":0.6714072202684293,"score_spread":0.07708143267115097,"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."}}