{"id":"W2027773481","doi":"10.1016/j.scitotenv.2006.12.003","title":"Feeding the city: Food consumption and flow of nitrogen, Paris, 1801–1914","year":2007,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"French Urban and Social Studies","field":"Social Sciences","cited_by":164,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Per capita; Forage; Population; Nitrogen; Geography; Consumption (sociology); Quarter (Canadian coin); Agricultural economics; Agriculture; Food consumption; Environmental science; Animal science; Toxicology; Agricultural science; Biology; Agronomy; Chemistry; Economics; Environmental health; Archaeology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.002877888,0.00007153168,0.0001066612,0.00001953088,0.001505694,0.00002744481,0.0004647872,0.00002946944,0.00004570953],"category_scores_gemma":[0.0001334557,0.00003592013,0.00006038176,0.000197739,0.006875002,0.00008613572,0.0002989321,0.000094329,0.000004098558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001300824,"about_ca_system_score_gemma":0.00003507314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007873165,"about_ca_topic_score_gemma":0.00009913171,"domain_scores_codex":[0.998619,0.00007354387,0.0001687945,0.0001342438,0.0007370412,0.0002674156],"domain_scores_gemma":[0.9994289,0.0001651006,0.000146073,0.0001953664,0.00001548376,0.00004907279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001377068,0.0006563095,0.03443327,0.00007606299,0.0004214809,0.000001645708,0.4540391,0.003654581,0.08149423,0.3601394,0.002491449,0.06245473],"study_design_scores_gemma":[0.0009710201,0.0004966864,0.7930454,0.0001223343,0.0003057269,0.000007468608,0.07223185,0.001074276,0.05351478,0.06787016,0.009699882,0.0006604153],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889313,0.001558913,0.00004516452,0.001739559,0.000259609,0.0002591266,0.00000440781,0.000006455053,0.007195485],"genre_scores_gemma":[0.9988511,0.0006017741,0.00008282506,0.00002452572,0.00007112524,0.000003376566,6.631792e-8,0.000002557625,0.0003626232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7586121,"threshold_uncertainty_score":0.9997942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0317605844393609,"score_gpt":0.2390834493565824,"score_spread":0.2073228649172215,"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."}}