{"id":"W4256701566","doi":"10.5539/jas.v13n1p202","title":"Reviewer Acknowledgements for Journal of Agricultural Science, Vol. 13, No. 1","year":2020,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Medical Research and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Library science; Regional science; Political science; Geography; Computer science; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002110603,0.0001782756,0.0005505689,0.00017979,0.0003090443,0.0001434836,0.0008965775,0.00004585043,0.0002892376],"category_scores_gemma":[0.07263567,0.00007193673,0.0003332495,0.002027649,0.001023936,0.001240689,0.0001370509,0.0004161067,0.0001494602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003313334,"about_ca_system_score_gemma":0.001235488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001636903,"about_ca_topic_score_gemma":0.000001240758,"domain_scores_codex":[0.9953578,0.00003772498,0.0008444949,0.0002365613,0.002930225,0.0005932073],"domain_scores_gemma":[0.9482073,0.000102092,0.0007738135,0.0001060037,0.04903105,0.001779698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002881752,0.0005250557,0.004794898,0.0002373211,0.000154711,0.00005941652,0.0004840777,0.000008535567,0.1889192,0.00003685204,0.7936108,0.01088105],"study_design_scores_gemma":[0.006422381,0.009453222,0.8744534,0.001546182,0.0003868232,0.0004887982,0.001110533,0.0000467334,0.03491748,0.00005456893,0.07081433,0.0003055804],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850545,0.001957234,0.0001316873,0.004480005,0.005990009,0.0006200012,0.000006368056,0.000008138729,0.00175204],"genre_scores_gemma":[0.9814727,0.001087584,0.005691174,0.0008348335,0.008381964,0.000005528717,0.000002856825,0.000008002089,0.002515364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8696585,"threshold_uncertainty_score":0.9351759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04146184146690129,"score_gpt":0.3466918307443579,"score_spread":0.3052299892774566,"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."}}