{"id":"W7028700221","doi":"","title":"Feature Story: Federal funding for research at the University of Regina","year":2014,"lang":"en","type":"other","venue":"oURspace (University of Regina)","topic":"Biomedical and Chemical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Feature (linguistics); Graduate research; Research council; Graduate students; Natural (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003048897,0.0005979739,0.0004807058,0.0006425143,0.005757147,0.00605882,0.002011379,0.0109973,0.1249368],"category_scores_gemma":[0.007877721,0.0003641967,0.0008258978,0.0009246758,0.00152499,0.002336971,0.002697939,0.006386514,0.04616587],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004295756,"about_ca_system_score_gemma":0.01116076,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07839385,"about_ca_topic_score_gemma":0.1171639,"domain_scores_codex":[0.9971317,0.0003993078,0.00006531271,0.0002895881,0.001184419,0.0009297412],"domain_scores_gemma":[0.9971915,0.000560968,0.0001198373,0.0002708345,0.000836773,0.001020166],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002264941,0.00000824306,0.0001358654,0.00001704302,0.000002562126,0.00004843122,0.0000394795,0.00001160788,0.0000548366,0.003563078,0.9908636,0.0052326],"study_design_scores_gemma":[0.000005613688,0.000007095332,0.0005581236,0.00002834397,0.000002234803,0.00003689795,0.0001248325,0.00001381644,0.00008309618,0.0002797861,0.9988533,0.000006866788],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.003531787,0.006836105,0.0003424371,0.6376988,0.0387754,0.00008257756,0.003627105,0.0007953795,0.3083104],"genre_scores_gemma":[0.01502705,0.003281041,0.0003498202,0.1856079,0.004098893,0.00009582013,0.001644285,0.00031671,0.7895786],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9969511,"threshold_uncertainty_score":0.4179554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04845066470447676,"score_gpt":0.3012789472647036,"score_spread":0.2528282825602268,"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."}}