{"id":"W3105233041","doi":"","title":"The Value of Agricultural Data in Carbon Cycle Studies: A Case Study from Ontario","year":2009,"lang":"en","type":"article","venue":"AGU Spring Meeting Abstracts","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Agriculture; Value (mathematics); Agricultural economics; Environmental science; Economics; Geography; Statistics; Mathematics; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00220075,0.0001688934,0.0003983842,0.00003594224,0.001896534,0.000009143671,0.0003841169,0.0001018149,0.000002391607],"category_scores_gemma":[0.0008901127,0.0001092454,0.0000301079,0.0001198462,0.00003794961,0.00006361705,0.0005155594,0.0006984384,0.00001084988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004927326,"about_ca_system_score_gemma":0.0002178828,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9063749,"about_ca_topic_score_gemma":0.9860101,"domain_scores_codex":[0.9975079,0.0002832706,0.0008389528,0.0003684539,0.0001874548,0.0008140252],"domain_scores_gemma":[0.9971395,0.001598932,0.0004178411,0.0006509075,0.0001392902,0.00005355283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003044694,0.00028801,0.7306109,0.00002773674,0.0001576105,0.0007236564,0.2658166,0.001823287,0.0001156203,0.00001445165,0.00007492115,0.000316737],"study_design_scores_gemma":[0.0004752795,0.0001115008,0.7240934,0.0001300172,0.00003992855,0.000007257278,0.2748396,0.00002808783,0.000008770743,0.0000350859,0.0001389124,0.00009221509],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918328,0.000763,5.716455e-8,0.0003604924,0.0006881197,0.0008818036,0.000004998832,0.00003642697,0.005432326],"genre_scores_gemma":[0.9993552,0.00005782035,0.0001335222,0.00008721806,0.0002098803,0.00002721628,0.000003569766,0.000009514863,0.0001160761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07963518,"threshold_uncertainty_score":0.9994029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07367453699257547,"score_gpt":0.3805524939688103,"score_spread":0.3068779569762348,"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."}}