{"id":"W4321225883","doi":"10.1111/ecin.13140","title":"The long‐run agglomeration effects of early agriculture in Europe","year":2023,"lang":"en","type":"article","venue":"Economic Inquiry","topic":"Archaeology and ancient environmental studies","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Brock University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Economies of agglomeration; Agriculture; Context (archaeology); Economic geography; Middle East; Economics; Agricultural economics; Urban agglomeration; Geography; Economy; Archaeology; Economic growth","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001463089,0.00004885355,0.00006855339,0.00002156069,0.0001314878,0.000005137201,0.00008718703,0.00002496127,0.00004907364],"category_scores_gemma":[0.00001612506,0.00003059113,0.00001656977,0.00008442122,0.0002146521,0.00007187785,0.00002324369,0.0000548267,0.001056853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003603667,"about_ca_system_score_gemma":0.000005706306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00013828,"about_ca_topic_score_gemma":0.001364934,"domain_scores_codex":[0.9995912,0.00003973556,0.0001044972,0.0001019239,0.00002966046,0.0001329792],"domain_scores_gemma":[0.9997354,0.0001490137,0.00003859787,0.00005929214,0.000002022705,0.00001573791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009878793,0.000002791358,0.9859509,0.000006559947,0.000008645568,0.000008038359,0.001514807,0.001837689,0.00003299221,0.0001134989,0.00273738,0.007776818],"study_design_scores_gemma":[0.00009030134,0.00004989668,0.9971637,0.000005381195,0.000001617446,8.385712e-7,0.0001330828,0.000171902,0.0002793615,0.0002142193,0.001849889,0.00003984106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996929,0.0004887279,0.000002499809,0.0001901691,0.0008793154,0.00008112207,0.000003763518,0.00001095898,0.001414377],"genre_scores_gemma":[0.9982533,0.0007988049,0.000005137225,0.0000459125,0.0001265254,0.000001493867,0.000020955,0.000001014152,0.0007467831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01121277,"threshold_uncertainty_score":0.9997209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0106830136357283,"score_gpt":0.1990904870867063,"score_spread":0.188407473450978,"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."}}