{"id":"W1971824890","doi":"10.3138/jvme.34.3.330","title":"Harnessing Collective Knowledge to Create Global Public Goods for Education and Health","year":2007,"lang":"en","type":"article","venue":"Journal of Veterinary Medical Education","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Entertainment; Public relations; Work (physics); Discipline; Sociology; Knowledge management; Business; Political science; Engineering; Social science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008209643,0.0005746824,0.0006583724,0.004074572,0.003634783,0.01149913,0.001168412,0.002507077,0.01497763],"category_scores_gemma":[0.011709,0.0003125914,0.0008384359,0.00263695,0.009965531,0.0104977,0.01523924,0.002195577,0.002244082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001944697,"about_ca_system_score_gemma":0.00520818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001167302,"about_ca_topic_score_gemma":0.001929053,"domain_scores_codex":[0.9959186,0.002356443,0.0001315181,0.0004125547,0.0007425466,0.00043847],"domain_scores_gemma":[0.9894336,0.005303667,0.0008992691,0.002368773,0.0008037162,0.001191047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004087664,0.0001334322,0.004319002,0.0009602658,0.0002161726,0.0005802353,0.02371756,0.002167042,0.001785188,0.6248007,0.0295806,0.311699],"study_design_scores_gemma":[0.00002690753,0.00008180816,0.002135299,0.0006624142,0.00005555588,0.0002278367,0.009752834,0.001107877,0.0006913536,0.6768115,0.3084094,0.00003711642],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06614424,0.01268429,0.1161834,0.09011983,0.002325821,0.0003088847,0.0002854532,0.0006029991,0.7113451],"genre_scores_gemma":[0.8923815,0.01037842,0.05233492,0.004648221,0.001714217,0.0002868875,0.0002539708,0.000182744,0.03781915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9885009,"threshold_uncertainty_score":0.05010515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1227635272424197,"score_gpt":0.5123484914212798,"score_spread":0.3895849641788601,"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."}}