{"id":"W4284963292","doi":"10.1016/j.evalprogplan.2022.102116","title":"Differential elements of a successful agricultural innovation scaling-up model","year":2022,"lang":"en","type":"article","venue":"Evaluation and Program Planning","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Scaling; Differential (mechanical device); Agriculture; Business; Computer science; Transport engineering; Engineering; Mathematics; Geography; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006304013,0.0001001612,0.0001125476,0.00003075208,0.0005157513,0.00008202133,0.0001072855,0.00003464226,0.0008248623],"category_scores_gemma":[0.00005769731,0.00004024309,0.00002844225,0.0009073687,0.00002299288,0.0002497098,0.00009220275,0.0001414979,9.101747e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002384769,"about_ca_system_score_gemma":0.0000112855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003532948,"about_ca_topic_score_gemma":0.000006589918,"domain_scores_codex":[0.9986845,0.0001353603,0.000351074,0.0001913944,0.0004950944,0.0001425841],"domain_scores_gemma":[0.9992312,0.00006715172,0.0003319574,0.00002738274,0.0003178146,0.00002445253],"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":[0.00009973707,0.0002724087,0.0251587,0.00001347036,0.00005109476,4.56377e-7,0.0010484,0.003121978,0.1263536,0.002402972,0.00213045,0.8393467],"study_design_scores_gemma":[0.001224644,0.0009911103,0.6996723,0.00004476302,0.0001594631,0.00002625573,0.01219776,0.2638657,0.00312494,0.002218155,0.01584712,0.000627778],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978653,0.0001391303,0.00002512089,0.0004859895,0.0001221083,0.000494931,0.00003453491,0.00005170396,0.0007812183],"genre_scores_gemma":[0.9979448,0.00000525598,0.00043965,0.00007171925,0.00007067089,0.0001985991,0.001095173,6.432838e-7,0.0001735264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8387189,"threshold_uncertainty_score":0.9031664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1073695963929548,"score_gpt":0.3819957290654639,"score_spread":0.2746261326725091,"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."}}