{"id":"W7063932506","doi":"","title":"Agricultural Carbon Markets: A Case Study of Alberta","year":2022,"lang":"en","type":"other","venue":"","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Agriculture; Agricultural productivity; Carbon fibers; Work (physics); Climate change","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003466052,0.0001376491,0.0001833154,0.00005063491,0.00002898965,0.000007063288,0.00009386562,0.00002051338,0.04349637],"category_scores_gemma":[5.254531e-7,0.0001014364,0.00003744253,0.0001178055,0.000007682926,0.00001337978,0.0000754567,0.00009368109,0.00001327928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001021354,"about_ca_system_score_gemma":0.00001650476,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03038438,"about_ca_topic_score_gemma":0.002663571,"domain_scores_codex":[0.9994499,0.00002898318,0.0001373342,0.0001499108,0.000112549,0.0001213041],"domain_scores_gemma":[0.9996796,0.00001758262,0.0001035254,0.0001622479,0.000007125625,0.00002997021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003041934,0.001297781,0.6897923,0.0000636481,0.001171054,0.0001833726,0.005907186,0.000004863438,0.00007516536,0.000136171,0.2949541,0.006383938],"study_design_scores_gemma":[0.00662042,0.000767498,0.03816276,0.00009386078,0.0005132711,0.0001552902,0.09957976,0.0004235857,0.0007667012,0.0000199395,0.850333,0.002563945],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4984673,0.00001007746,1.249395e-7,0.000001521768,0.00006762004,0.0001576676,0.000004608269,0.00001123292,0.5012799],"genre_scores_gemma":[0.58444,2.898445e-7,0.000008062359,0.000001513525,0.00006877795,0.00003921194,0.00001276363,0.00003643131,0.4153929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6516296,"threshold_uncertainty_score":0.9760724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008347020855609115,"score_gpt":0.2222880832027108,"score_spread":0.2139410623471017,"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."}}