{"id":"W4408460399","doi":"10.21083/ruralreview.v4i1.5967","title":"Profiling Rural Research at SEDRD","year":2020,"lang":"en","type":"article","venue":"Rural Review Ontario Rural Planning Development and Policy","topic":"Rural development and sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Profiling (computer programming); Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01174367,0.000220533,0.0004053301,0.003844928,0.00984921,0.00510814,0.0009067169,0.001171002,0.01844454],"category_scores_gemma":[0.01566885,0.0005575532,0.0002416145,0.007123719,0.003653618,0.002229062,0.005670129,0.001100817,0.00209524],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03208673,"about_ca_system_score_gemma":0.05246896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1345278,"about_ca_topic_score_gemma":0.4685523,"domain_scores_codex":[0.9872799,0.006195692,0.0003538479,0.001154474,0.00324532,0.00177077],"domain_scores_gemma":[0.9771161,0.005846203,0.001556566,0.001538357,0.007859386,0.006083506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003220956,0.0001234024,0.04410976,0.001984346,0.00003898776,0.001706617,0.1997513,0.0005367818,0.009398607,0.1213321,0.1977774,0.4229185],"study_design_scores_gemma":[0.000007822077,0.00007240462,0.0254499,0.0002954301,0.000006216667,0.0001668221,0.02826083,0.00008191687,0.0006877831,0.002268276,0.9426842,0.00001840401],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.281734,0.03836964,0.01528975,0.09794956,0.001214439,0.001705344,0.00324521,0.0007977798,0.5596942],"genre_scores_gemma":[0.5996408,0.01715454,0.01707119,0.008790759,0.0003078218,0.0008905233,0.0008161084,0.0003559232,0.3549724],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9961551,"threshold_uncertainty_score":0.2674897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08342269681541736,"score_gpt":0.3307934109850627,"score_spread":0.2473707141696453,"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."}}