{"id":"W3088063721","doi":"","title":"Hydrologic Profiling for Greenhouse Gases from Prairie Potholes in Western Canada","year":2010,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Environmental science; Profiling (computer programming); Hydrology (agriculture); Geology; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001261638,0.0002118716,0.0002340865,0.0009789296,0.00183696,0.0008499783,0.0005952831,0.0003740675,0.001064479],"category_scores_gemma":[0.0003307248,0.0001765238,0.0002457619,0.001595019,0.0004316609,0.000368935,0.0003900286,0.0003287531,0.0001309191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009027835,"about_ca_system_score_gemma":0.009286456,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9856765,"about_ca_topic_score_gemma":0.995237,"domain_scores_codex":[0.9998486,0.000005297062,0.000005173191,0.00003142636,0.00005614897,0.00005343561],"domain_scores_gemma":[0.9997101,0.00002148889,0.00002509459,0.000009817785,0.0001744921,0.00005889189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003571929,0.0001974669,0.9182873,0.00009533826,0.0001301811,0.0009760282,0.004598163,0.009647008,0.03249412,0.0006662253,0.004382238,0.02816871],"study_design_scores_gemma":[0.00001255512,0.00001232898,0.9904317,0.000009615786,0.00001671356,0.00004045437,0.001627578,0.004337772,0.001167238,0.00003717467,0.002288872,0.0000180231],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953129,0.00006673979,0.000233887,0.00008225473,0.000004121032,0.00002679476,0.001584921,0.00005820565,0.00263012],"genre_scores_gemma":[0.9969385,0.00008005545,0.0005245901,0.00002452019,0.000002218869,0.00001156914,0.0007282788,0.00001322548,0.001677036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01432347,"threshold_uncertainty_score":0.06550187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009352979737787296,"score_gpt":0.2080210493246618,"score_spread":0.1986680695868745,"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."}}