{"id":"W6931145076","doi":"10.5281/zenodo.3775781","title":"Preserving the agricultural data story at the Ontario Agricultural College","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Agriculture; RDM; Variety (cybernetics); Christian ministry; Social research; Presentation (obstetrics); Research council; Applied research","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007776985,0.0003678702,0.0004411358,0.001602197,0.02542313,0.01367167,0.002114868,0.001897889,0.01818202],"category_scores_gemma":[0.02069867,0.000500914,0.0002547709,0.004927154,0.01501718,0.00770086,0.007277724,0.004243934,0.003278841],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0637795,"about_ca_system_score_gemma":0.04583484,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7224292,"about_ca_topic_score_gemma":0.861735,"domain_scores_codex":[0.9905956,0.002298568,0.0002259547,0.0009212453,0.004908487,0.001050262],"domain_scores_gemma":[0.9772584,0.006707693,0.0007789156,0.002479614,0.006774065,0.006001441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001404433,0.00004779692,0.003298241,0.0001739186,0.000009956695,0.0008134079,0.1222797,0.0003343157,0.001819814,0.05053364,0.7400872,0.08046158],"study_design_scores_gemma":[0.000003030838,0.00000430307,0.0006241523,0.00002754077,0.000001082647,0.00004154853,0.009506187,0.00006726303,0.0001761348,0.00112489,0.9884095,0.00001427664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07103126,0.009350502,0.01415672,0.4610641,0.004751739,0.0004691222,0.004336343,0.001794398,0.4330458],"genre_scores_gemma":[0.4667232,0.009304231,0.01643482,0.03319384,0.001606442,0.000486516,0.002416077,0.001981221,0.4678536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9863283,"threshold_uncertainty_score":0.5584109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05800143300932929,"score_gpt":0.2410828996120538,"score_spread":0.1830814666027245,"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."}}