{"id":"W4392600444","doi":"10.5194/egusphere-egu24-6070","title":"Reconciling climate change mitigation, biodiversity conservation and rice production through changes in water management strategies","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Agriculture, Water, and Health","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Continental (Canada)","funders":"","keywords":"Climate change; Production (economics); Biodiversity; Biodiversity conservation; Natural resource economics; Environmental resource management; Water conservation; Environmental science; Environmental planning; Agroforestry; Business; Economics; Ecology; Water resources","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003629392,0.0001933876,0.0001628114,0.00005059154,0.0001446569,0.0001130398,0.00009579376,0.0001497239,0.0001414951],"category_scores_gemma":[0.000001526202,0.0001303907,0.00002253828,0.0001010316,0.00008404443,0.0002959429,0.0009096974,0.0002473798,0.0002403611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002462241,"about_ca_system_score_gemma":0.00000460792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003917535,"about_ca_topic_score_gemma":0.009426123,"domain_scores_codex":[0.998679,0.00004867436,0.0001908379,0.0006178195,0.0001845547,0.0002791578],"domain_scores_gemma":[0.9997318,0.000005220332,0.00006322507,0.0001507784,0.0000120749,0.00003689932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003407478,0.0008176768,0.5177171,0.03557246,0.0003991641,0.0002483076,0.3209663,0.003050611,0.01209167,0.01608076,0.06699364,0.02572156],"study_design_scores_gemma":[0.0006602212,0.0001477417,0.7864214,0.001105677,0.0002534107,0.00002294674,0.02957402,0.0006600888,0.01892289,0.1497065,0.01091054,0.001614563],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764721,0.000149496,0.00001792461,0.01336306,0.0005739791,0.001003839,0.00001844493,0.0001026722,0.008298518],"genre_scores_gemma":[0.9854473,0.009769492,0.001864881,0.001349389,0.0002500924,0.0002086572,0.0003461729,0.00001178611,0.0007522493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2913923,"threshold_uncertainty_score":0.5922167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04161389427748911,"score_gpt":0.2506039170282947,"score_spread":0.2089900227508055,"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."}}