{"id":"W4411209735","doi":"10.1016/j.agrformet.2025.110678","title":"A process model-guided transfer learning framework for mapping global gross primary production","year":2025,"lang":"en","type":"article","venue":"Agricultural and Forest Meteorology","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Primary (astronomy); Production (economics); Process (computing); Environmental science; Primary production; Computer science; Physics; Economics; Programming language","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":[0.001336785,0.0002068972,0.000454769,0.0001420023,0.000531404,0.0001450541,0.0003885964,0.0002261492,0.000006897837],"category_scores_gemma":[0.002285536,0.0001174905,0.0001731026,0.001560573,0.000198818,0.0003030582,0.00007069253,0.000234059,0.000007442042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005205768,"about_ca_system_score_gemma":0.00005836982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001585522,"about_ca_topic_score_gemma":0.00008627935,"domain_scores_codex":[0.9976481,0.0001554933,0.0006018013,0.0007872874,0.0004075176,0.0003997526],"domain_scores_gemma":[0.9985871,0.000505855,0.0001191529,0.0002061155,0.0005146535,0.00006712056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004178537,0.0002737924,0.1469584,0.0002066779,0.0003366487,0.000004915338,0.00340006,0.5491779,0.008423075,0.2444656,0.004259058,0.04207602],"study_design_scores_gemma":[0.0006043399,0.0002020452,0.3197097,0.00007164667,0.0002026278,0.00006638643,0.001252663,0.04575789,0.0004280432,0.6295695,0.001712873,0.0004222372],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7975881,0.0003038722,0.1960797,0.004621784,0.0002913704,0.0003276507,0.000005101715,0.00006517652,0.0007172943],"genre_scores_gemma":[0.9931899,0.00001717979,0.004922722,0.0004718697,0.0001090081,0.00007695616,0.00001868594,0.000004094182,0.001189574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.50342,"threshold_uncertainty_score":0.4791122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04972967560771329,"score_gpt":0.3479947167391262,"score_spread":0.2982650411314129,"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."}}