{"id":"W4200053492","doi":"10.26721/spafa.pqcnu8815a-09","title":"Before Bagan: Using Archaeological Data Sets to Assess the Traditional Historical Narrative | ပဂမတငမကလ၏အစဉအလသမငအဆအမနမက ရရငသရတသ နပညပဆငအခကအလကမအသပပ၍ဆနစစပခင","year":2021,"lang":"my","type":"article","venue":"","topic":"Eurasian Exchange Networks","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Social Sciences and Humanities Research Council of Canada; Trent University","keywords":"Narrative; Settlement (finance); Excavation; Presentation (obstetrics); History; Archaeology; Scale (ratio); Computer science; Geography; Art; Literature; Cartography; World Wide Web; Medicine","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002618336,0.0007011508,0.0009363422,0.0001390201,0.002633982,0.0004175895,0.003225092,0.000749519,0.008293544],"category_scores_gemma":[0.001829715,0.0005380465,0.0003237068,0.002366968,0.001394579,0.0008993437,0.002349434,0.001550435,0.0002323622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002217062,"about_ca_system_score_gemma":0.001753328,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001384143,"about_ca_topic_score_gemma":0.02003559,"domain_scores_codex":[0.9903097,0.002739164,0.0009816134,0.002035903,0.002258623,0.001675032],"domain_scores_gemma":[0.9946686,0.001530403,0.0003415458,0.001888765,0.0006042569,0.0009664246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002276321,0.001717666,0.01124773,0.0001068974,0.0007387248,0.002478825,0.3274352,0.000743077,0.0002961823,0.1103145,0.5175785,0.02711505],"study_design_scores_gemma":[0.001608816,0.0009661836,0.02757876,0.0005283209,0.0006499364,0.0006403459,0.1785396,0.03259227,0.00008070448,0.02848686,0.7254142,0.00291408],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4435159,0.006003656,0.03059266,0.41267,0.02134584,0.004243399,0.00216129,0.0008032795,0.07866392],"genre_scores_gemma":[0.9448635,0.0002287132,0.01671402,0.008557904,0.00960905,0.00007211156,0.0008995051,0.000117356,0.01893785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5013476,"threshold_uncertainty_score":0.9997071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4386891093928131,"score_gpt":0.4039575918933336,"score_spread":0.0347315174994795,"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."}}