{"id":"W4411652037","doi":"10.21248/gups.90898","title":"Analyzing the global impacts of food and feed production, trade and consumption on terrestrial and marine ecosystems","year":2025,"lang":"en","type":"dissertation","venue":"","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Consumption (sociology); Production (economics); Ecosystem; Marine ecosystem; Terrestrial ecosystem; Environmental science; Natural resource economics; Business; Ecology; Economics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004568395,0.0003423065,0.0001973013,0.001042439,0.0003274769,0.00189231,0.0002265713,0.0004699267,0.001872916],"category_scores_gemma":[0.001129924,0.0001203333,0.0006381572,0.002895999,0.000700595,0.001223441,0.001154236,0.0005154123,0.0002255845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001168082,"about_ca_system_score_gemma":0.0007303168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007708183,"about_ca_topic_score_gemma":0.008664965,"domain_scores_codex":[0.9998042,0.00005403856,0.000008089261,0.00002906933,0.00005681655,0.00004776615],"domain_scores_gemma":[0.9993444,0.0003535307,0.0001463631,0.00003795413,0.00008124735,0.00003640203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001542324,0.0001693833,0.513543,0.001626732,0.0009432145,0.001753196,0.003832758,0.1542253,0.007730391,0.1094509,0.01130477,0.1952662],"study_design_scores_gemma":[0.00001015863,0.0002625431,0.802475,0.0008151599,0.0004500577,0.0005494438,0.0145227,0.04026994,0.005030531,0.06480958,0.07072669,0.00007814597],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9482953,0.006695198,0.004400131,0.003908216,0.000101129,0.00002549881,0.001317506,0.00002672515,0.03523017],"genre_scores_gemma":[0.9799337,0.01309164,0.002845087,0.0003246628,0.00006130209,0.00002826362,0.0006227111,0.00002414854,0.003068469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007708183,"threshold_uncertainty_score":0.01532668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744094376848881,"score_gpt":0.2404074419050544,"score_spread":0.2229664981365656,"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."}}