{"id":"W4313446910","doi":"10.1525/collabra.57545","title":"Ten Strategies to Foster Open Science in Psychology and Beyond","year":2022,"lang":"en","type":"article","venue":"Collabra Psychology","topic":"Research Data Management Practices","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Open science; Openness to experience; Citizen science; Open data; Best practice; Obstacle; Engineering ethics; Open research; Workflow; Public relations; Dissemination; Political science; Computer science; Psychology; Engineering; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.003680946,0.0001347722,0.0002050201,0.0009587825,0.0004082114,0.002739487,0.01099661,0.00003446774,0.0001604982],"category_scores_gemma":[0.0002182068,0.0001395902,0.00001246483,0.003447364,0.0003313961,0.01360672,0.01479544,0.0003247752,0.00005443397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006254109,"about_ca_system_score_gemma":0.0002535867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004240284,"about_ca_topic_score_gemma":0.0001437458,"domain_scores_codex":[0.9968013,0.0004531796,0.0002737743,0.001362728,0.0004677755,0.0006413031],"domain_scores_gemma":[0.9977071,0.0001516479,0.00009409442,0.001808821,0.00006528314,0.0001730717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003559067,0.0006926795,0.007841213,0.00001909528,0.00003188287,0.0006033502,0.002959653,0.0001042816,0.009544542,0.5427259,0.1525948,0.2825266],"study_design_scores_gemma":[0.001826682,0.001413923,0.1136464,0.000004299943,0.000003354352,0.0001883419,0.0009506249,0.0004756199,0.0000347096,0.03351982,0.8475675,0.000368731],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1117816,0.0005955253,0.05586466,0.2606551,0.002710851,0.002882341,0.00003123059,0.0001453217,0.5653333],"genre_scores_gemma":[0.8454282,0.0003959198,0.06983703,0.08037286,0.00005870389,0.001083616,0.000009217296,0.00002928353,0.002785118],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7336466,"threshold_uncertainty_score":0.9982958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1193344933773208,"score_gpt":0.4602390211546548,"score_spread":0.340904527777334,"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."}}