{"id":"W2559959546","doi":"10.1371/journal.pbio.2001259","title":"Accelerating Translational Research through Open Science: The Neuro Experiment","year":2016,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Genome Alberta; Alberta Innovates; Genome Canada","keywords":"Translational research; Open science; Translational science; Biology; Institution; Open research; Citizen science; Data science; Engineering ethics; Public relations; Sociology; Political science; Computer science; Ecology; Social science; Engineering; Biotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003994133,0.00006232585,0.000141328,0.00007514696,0.0004585283,0.00003615481,0.0006513965,0.00006351154,0.0008872577],"category_scores_gemma":[0.0361582,0.00002527003,0.00001993779,0.0003714325,0.001363516,0.0001396294,0.0002873897,0.0003223171,0.0001406747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001026465,"about_ca_system_score_gemma":0.005410881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001147505,"about_ca_topic_score_gemma":0.00001028948,"domain_scores_codex":[0.9975964,0.0002420681,0.0001875215,0.0003040432,0.0006687126,0.001001247],"domain_scores_gemma":[0.9964303,0.001786382,0.00002248069,0.0003290437,0.0002995561,0.001132194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003219857,0.0002321839,0.00568277,0.00002569235,0.00001816811,0.00001618189,0.0008246106,3.263083e-8,0.8496946,0.02501711,0.01358093,0.1045858],"study_design_scores_gemma":[0.005796773,0.004223927,0.02335004,0.0003797809,0.00001342762,0.00007546402,0.0004420507,0.0003459091,0.2644006,0.01904542,0.6817147,0.0002119552],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5241507,0.0003115392,0.000405877,0.4406152,0.0001401781,0.00144664,0.000008202119,0.00002490909,0.03289674],"genre_scores_gemma":[0.9894286,0.0001218892,0.0007261061,0.008969638,0.0003306358,0.0001236746,0.000002931462,0.000007340987,0.0002891228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6681337,"threshold_uncertainty_score":0.9719607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6992957652743598,"score_gpt":0.6059189416587737,"score_spread":0.09337682361558608,"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."}}