{"id":"W4242712010","doi":"10.5539/jas.v11n11p312","title":"Reviewer Acknowledgements for Journal of Agricultural Science, Vol. 11, No. 11, Special Issue","year":2019,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Library science; Regional science; Engineering ethics; Sociology; Computer science; History; Engineering; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003742676,0.0004474695,0.000854707,0.0001183165,0.0008977976,0.0006134889,0.00255221,0.0001289636,0.001439604],"category_scores_gemma":[0.006896874,0.0001296844,0.0006355764,0.002960537,0.0008034888,0.004202638,0.0003687645,0.0004155025,0.0003112537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004706716,"about_ca_system_score_gemma":0.0002186183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001352859,"about_ca_topic_score_gemma":0.00007074578,"domain_scores_codex":[0.9943467,0.00009539682,0.001468139,0.0006094876,0.002468228,0.001012033],"domain_scores_gemma":[0.9545728,0.0001706485,0.002130614,0.0001379328,0.04241965,0.0005683669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000464677,0.0003020153,0.002390061,0.00004367658,0.0000288879,0.000001762737,0.000183066,0.00004141313,0.7125915,0.00006438618,0.2749259,0.009380946],"study_design_scores_gemma":[0.00081006,0.002342252,0.5635802,0.0003187922,0.0001039492,0.0001176546,0.002081871,0.000004286404,0.05769361,0.00007815868,0.3723168,0.0005523838],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703113,0.0003516117,0.000003201048,0.001407247,0.02598636,0.0008255559,0.00001884186,0.00001511552,0.001080758],"genre_scores_gemma":[0.918031,0.0003057501,0.001167975,0.0003255228,0.06793792,0.0000103755,0.00001106679,0.000003767988,0.01220659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6548978,"threshold_uncertainty_score":0.9994732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541455488490322,"score_gpt":0.2436916195984093,"score_spread":0.2282770647135061,"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."}}