{"id":"W4402081220","doi":"10.2139/ssrn.4943042","title":"A Process Model-Guided Transfer Learning Framework for Mapping Global Gross Primary Production","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Water resources management and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Process (computing); Primary (astronomy); Production (economics); Computer science; Economics; Macroeconomics; Physics","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":[0.001369316,0.0007130461,0.001026045,0.0005485472,0.0004084983,0.0009568941,0.001685363,0.001500578,0.003398529],"category_scores_gemma":[0.002797006,0.0004375048,0.0007920812,0.000810585,0.0007544567,0.001200338,0.001399956,0.001532539,0.0005180187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057098,"about_ca_system_score_gemma":0.001864749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01669167,"about_ca_topic_score_gemma":0.009217336,"domain_scores_codex":[0.999732,0.0001084647,0.00001031317,0.00006611379,0.00004607926,0.00003699138],"domain_scores_gemma":[0.9992435,0.0005156653,0.00005196796,0.00005145292,0.0001040031,0.00003342312],"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":[0.00002454354,0.00002675198,0.0001533736,0.00001719515,0.00001772829,0.0000179325,0.00001777877,0.9776841,0.0003235396,0.005384757,0.0003085403,0.0160238],"study_design_scores_gemma":[0.000001962855,0.000004792857,0.00002108365,8.986364e-7,0.000001415347,0.000001309994,0.00000112983,0.9974787,0.00004901403,0.002384831,0.00005368414,0.000001182723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01448642,0.0001387881,0.983067,0.0001757125,0.00002306975,0.00003025921,0.00007952331,0.0004195829,0.001579592],"genre_scores_gemma":[0.828667,0.000242055,0.1650183,0.000127192,0.00007915675,0.0002617858,0.0003594068,0.0001830734,0.005062057],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01669167,"threshold_uncertainty_score":0.033189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142928735289406,"score_gpt":0.2440546129901932,"score_spread":0.2297617394612526,"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."}}