{"id":"W2916371782","doi":"10.5334/kula.9","title":"Developing an Open Social Scholarship Collaboration: Lessons from INKE","year":2019,"lang":"en","type":"article","venue":"KULA knowledge creation dissemination and preservation studies","topic":"Research Data Management Practices","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Scholarship; Process (computing); Work (physics); Engineering ethics; Reflection (computer programming); Engaged scholarship; Best practice; Public relations; Sociology; Psychology; Medical education; Pedagogy; Political science; Engineering; Computer science; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.07787928,0.0007083862,0.0009269269,0.003894889,0.02567939,0.03312489,0.005665859,0.006404458,0.004673347],"category_scores_gemma":[0.1005576,0.0009347132,0.00116462,0.004031017,0.03528082,0.04045206,0.04873633,0.009239973,0.001698383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007593135,"about_ca_system_score_gemma":0.02029447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003294708,"about_ca_topic_score_gemma":0.006984858,"domain_scores_codex":[0.8864678,0.09262973,0.002862326,0.002743178,0.008531078,0.006765986],"domain_scores_gemma":[0.8416974,0.1053241,0.005422895,0.01942967,0.01072213,0.01740384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006226184,0.0004267945,0.004425493,0.0005855659,0.00002815285,0.002402771,0.789976,0.0003549781,0.000367223,0.08481467,0.008327174,0.108229],"study_design_scores_gemma":[0.00004056346,0.0001875701,0.001530471,0.0008781972,0.00001058712,0.001231397,0.755264,0.0004173066,0.0005084793,0.06152315,0.1783509,0.00005741712],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.401599,0.006235915,0.0928218,0.2490048,0.001682621,0.001641122,0.0001477888,0.0009748154,0.2458921],"genre_scores_gemma":[0.9122435,0.00345562,0.05791713,0.006811812,0.0003828664,0.000782266,0.0001148242,0.0004727795,0.01781925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9943342,"threshold_uncertainty_score":0.4118699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3065988656627029,"score_gpt":0.5259031172388531,"score_spread":0.2193042515761502,"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."}}