{"id":"W4393011730","doi":"10.1017/ehs.2024.5","title":"Climate, climate change and the global diversity of human houses","year":2024,"lang":"en","type":"article","venue":"Evolutionary Human Sciences","topic":"Architecture and Cultural Influences","field":"Arts and Humanities","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Vernacular; Architecture; Climate change; Diversity (politics); Geography; Vernacular architecture; Roof; Variation (astronomy); Architectural engineering; Economic geography; Ecology; Sociology; Archaeology; Engineering; Linguistics; Anthropology","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0003507537,0.000104228,0.0001298363,0.00004697209,0.003874879,0.000175235,0.0002980037,0.0000195084,0.0004182854],"category_scores_gemma":[0.000005949618,0.00005498452,0.00007344939,0.00009570276,0.004398755,0.0005207979,0.0004105289,0.00006826509,0.00001992882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000163327,"about_ca_system_score_gemma":0.00001048115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007607734,"about_ca_topic_score_gemma":0.001447463,"domain_scores_codex":[0.9990668,0.00005621281,0.0001580411,0.0002204233,0.0002773284,0.0002211532],"domain_scores_gemma":[0.9997405,0.00005739691,0.00005334643,0.00007961638,0.00003842665,0.00003073838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007330245,0.00001153459,0.009222341,0.00004359845,0.00001082825,0.000002247824,0.02034775,0.000001711529,0.0000119897,0.9685152,0.001447792,0.0003777247],"study_design_scores_gemma":[0.0008803693,0.0009646406,0.2639619,0.0006693816,0.0002235097,0.00005860992,0.03695432,0.0003976705,0.0000345255,0.6382781,0.05679338,0.0007836071],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8957455,0.007581032,5.61882e-7,0.001237866,0.0003252652,0.0001825677,0.0001321753,0.0001200723,0.09467493],"genre_scores_gemma":[0.9990065,0.0001606143,0.00001381417,0.0002280843,0.0003745035,0.000009809037,0.000004098848,0.000002380246,0.0002002335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3302371,"threshold_uncertainty_score":0.9983107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0896984000000246,"score_gpt":0.2927685002733885,"score_spread":0.2030701002733639,"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."}}