{"id":"W2515291001","doi":"10.1177/0270467616668760","title":"How Do Scientists Define Openness? Exploring the Relationship Between Open Science Policies and Research Practice","year":2016,"lang":"en","type":"article","venue":"Bulletin of Science Technology & Society","topic":"Research Data Management Practices","field":"Computer Science","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Economic and Social Research Council","keywords":"Openness to experience; Open science; Science policy; Government (linguistics); Political science; Research policy; Public relations; Best practice; Engineering ethics; Sociology; Psychology; Public administration; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2195321,0.0004165831,0.00101074,0.006413796,0.01652592,0.02897727,0.002565372,0.006331814,0.001612182],"category_scores_gemma":[0.4010808,0.000960147,0.0006581333,0.007387463,0.09259032,0.03451135,0.0311802,0.009918759,0.0002346771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02230159,"about_ca_system_score_gemma":0.03496539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006715975,"about_ca_topic_score_gemma":0.004653996,"domain_scores_codex":[0.6245174,0.3194469,0.01342504,0.009058838,0.02253138,0.0110205],"domain_scores_gemma":[0.3254227,0.578052,0.04912825,0.01859482,0.01740872,0.01139368],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004982216,0.00007440802,0.02225094,0.0002623693,0.00003914377,0.0001811749,0.8260322,0.0003261933,0.0002702427,0.137641,0.000661818,0.01221066],"study_design_scores_gemma":[0.00002741043,0.00006170836,0.01097041,0.0008700689,0.00002236349,0.0001524818,0.8178018,0.0004870222,0.000385419,0.137429,0.03172066,0.00007171065],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7459309,0.005081225,0.02850476,0.1330029,0.0003626335,0.0002977359,0.00008553679,0.00006196924,0.08667234],"genre_scores_gemma":[0.9962962,0.0005456306,0.00144341,0.001329992,0.00002846466,0.00009607775,0.00001006811,0.00001411542,0.0002359365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9974346,"threshold_uncertainty_score":0.9624558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3020403008169142,"score_gpt":0.4386357982622262,"score_spread":0.1365954974453119,"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."}}