{"id":"W323244149","doi":"10.1007/s12520-015-0245-4","title":"Drivers of technological richness in prehistoric Texas: an archaeological test of the population size and environmental risk hypotheses","year":2015,"lang":"en","type":"article","venue":"Archaeological and Anthropological Sciences","topic":"Archaeology and ancient environmental studies","field":"Earth and Planetary Sciences","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Species richness; Population; Population size; Geography; Prehistory; Ecology; Bivariate analysis; Demography; Archaeology; Biology; Statistics; Sociology; Mathematics","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":[0.0003344013,0.00008248063,0.00008508622,0.0006595803,0.0006466734,0.0006452792,0.0002994102,0.0002234954,0.002274055],"category_scores_gemma":[0.001314728,0.0001462291,0.00009436907,0.0008209512,0.000842717,0.0006701774,0.0005581322,0.0003708153,0.00008555576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005632663,"about_ca_system_score_gemma":0.0004442899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01985402,"about_ca_topic_score_gemma":0.05002825,"domain_scores_codex":[0.9998701,0.00002949426,0.000006539954,0.00003550569,0.00001455577,0.00004386003],"domain_scores_gemma":[0.9986333,0.0004648522,0.0005774235,0.00008902583,0.00009883229,0.0001366501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007098213,0.00005507057,0.9876385,0.000008797343,0.000025676,0.0001344802,0.004465417,0.0004014993,0.001091952,0.002188008,0.0001289932,0.003790575],"study_design_scores_gemma":[0.000002895242,0.00002044327,0.9931445,0.000004852023,0.000008124354,0.00005043812,0.005278027,0.0006390949,0.00009650987,0.0003965794,0.000355164,0.000003423949],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995772,0.00000826019,0.00003651546,0.00005412856,2.856877e-7,8.188389e-7,0.00002677095,4.369444e-7,0.0002956338],"genre_scores_gemma":[0.9998122,0.00001112563,0.00003371208,0.000004490921,0.000001223378,0.000001118457,0.00002018202,3.594589e-7,0.000115765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01985402,"threshold_uncertainty_score":0.03947687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259981187609399,"score_gpt":0.2241873760344738,"score_spread":0.2015875641583798,"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."}}