{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001018179,0.0004271196,0.0006185029,0.00004460114,0.001081161,0.0001657602,0.0004578133,0.0001491799,0.0006070505],"category_scores_gemma":[0.0003103585,0.0001876221,0.000133733,0.0008919541,0.0001386252,0.0003316388,0.0004441772,0.0005827332,0.0002863539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006845352,"about_ca_system_score_gemma":0.0003538219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004421052,"about_ca_topic_score_gemma":0.003314369,"domain_scores_codex":[0.9968461,0.0002163562,0.000731891,0.0004265703,0.0007102145,0.001068825],"domain_scores_gemma":[0.9987488,0.0002286021,0.0001502915,0.00009550263,0.0001992132,0.0005775556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003140758,0.00007329325,0.6528738,0.001488481,0.0001184107,0.00007517389,0.008901672,0.000002233663,0.01564289,0.00159805,0.05838817,0.2605238],"study_design_scores_gemma":[0.0002920069,0.0001940309,0.418649,0.001400004,0.00001895288,0.00003096927,0.001574972,0.000007283848,0.001297122,0.0003011182,0.5755348,0.0006997142],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621264,0.009569976,4.058621e-7,0.02454138,0.00007730801,0.0009249906,0.000007167141,0.0001327162,0.002619701],"genre_scores_gemma":[0.9819587,0.002845032,0.0004724583,0.005460021,0.0005943659,0.000118581,0.0006141866,0.0000065309,0.007930085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5171466,"threshold_uncertainty_score":0.8315522,"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."}}