{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001789564,0.0006312531,0.001081142,0.0006638922,0.0004454396,0.0009913188,0.001651723,0.001257706,0.002903477],"category_scores_gemma":[0.003003192,0.0004282382,0.0007355518,0.0008500622,0.0006987346,0.001200317,0.001201907,0.001372133,0.0003468734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001396208,"about_ca_system_score_gemma":0.002315286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02157846,"about_ca_topic_score_gemma":0.01312272,"domain_scores_codex":[0.999671,0.000129208,0.00001535093,0.00007511376,0.00006259408,0.00004674811],"domain_scores_gemma":[0.9990397,0.000673511,0.00006140902,0.00004811259,0.000141846,0.00003539321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001703442,0.00002928389,0.0001831776,0.00001221157,0.00001608728,0.00001202049,0.00001296692,0.9814748,0.0002153204,0.004707047,0.0002093058,0.01311069],"study_design_scores_gemma":[0.000001532505,0.000003400811,0.00002223859,6.977629e-7,0.000001205761,9.203744e-7,0.00000103214,0.9982734,0.00003636094,0.001616299,0.00004214493,8.240919e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01859636,0.0001243532,0.9790354,0.0001772809,0.00001548431,0.00003956429,0.00009104115,0.0003345614,0.001586011],"genre_scores_gemma":[0.8259701,0.000184359,0.1691123,0.0001042005,0.00004915928,0.0003100025,0.0003389708,0.0001300044,0.003801008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02157846,"threshold_uncertainty_score":0.04290575,"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."}}