{"id":"W1627084369","doi":"","title":"Urban food planning and transport sustainability: A case study in Parma, Italy","year":2011,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Organic Food and Agriculture","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Sustainability; Business; Environmental planning; Urban sustainability; Baseline (sea); Order (exchange); Food supply; Urban planning; Food systems; Environmental economics; Environmental resource management; Geography; Food security; Economics; Agricultural economics; Engineering; Civil engineering; Political science","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":[0.0008563293,0.0006411842,0.0003425819,0.0008151702,0.001876359,0.001582018,0.001190046,0.001756979,0.004185681],"category_scores_gemma":[0.001766633,0.0003131922,0.0005651063,0.003271244,0.001236074,0.0008236572,0.001260606,0.0008272369,0.0003566997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004410821,"about_ca_system_score_gemma":0.001498491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06695917,"about_ca_topic_score_gemma":0.1194428,"domain_scores_codex":[0.9990753,0.0005768214,0.00001558631,0.00007035541,0.00005643358,0.0002055094],"domain_scores_gemma":[0.9992192,0.000443007,0.0001044242,0.00005960307,0.00004806923,0.000125595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001545497,0.01051212,0.3022955,0.002195168,0.0005542639,0.1780067,0.07734859,0.1667969,0.004796345,0.05263648,0.03101784,0.1722945],"study_design_scores_gemma":[0.0005556597,0.003468086,0.5320253,0.0005191562,0.000395105,0.0111853,0.2137205,0.09329579,0.002807449,0.01060107,0.1311447,0.0002817324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835559,0.0003160257,0.001129356,0.0006733352,0.00001590823,0.0001842374,0.0002651734,0.00002525749,0.01383482],"genre_scores_gemma":[0.9936726,0.0006187569,0.001598914,0.00008374362,0.00001910055,0.0001309936,0.0001944121,0.00001474203,0.003666794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06695917,"threshold_uncertainty_score":0.1331388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04187432095451731,"score_gpt":0.2695268930023606,"score_spread":0.2276525720478433,"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."}}