{"id":"W6969455424","doi":"10.5284/1099605","title":"Eversley, London Road, Sawbridgeworth, Herts","year":2015,"lang":"en","type":"article","venue":"Archaeology Data Service","topic":"Business, Innovation, and Economy","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage","funders":"","keywords":"Trench; Land use; World heritage; Archaeological evidence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007489235,0.0008204139,0.0005209441,0.001634172,0.002584871,0.004460229,0.001197331,0.002151078,0.4721348],"category_scores_gemma":[0.003581885,0.0007203028,0.0005331333,0.002502589,0.001409856,0.002662916,0.002043145,0.001191527,0.05853707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004707003,"about_ca_system_score_gemma":0.003401636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06346028,"about_ca_topic_score_gemma":0.2846649,"domain_scores_codex":[0.9988237,0.0001641977,0.00008873737,0.0004130992,0.0003245049,0.0001858128],"domain_scores_gemma":[0.9964752,0.001369748,0.0004046239,0.000308365,0.0007361142,0.0007059704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.002056101,0.0002202824,0.03854903,0.002695553,0.0002199364,0.01781766,0.007811772,0.002144309,0.009864422,0.02711674,0.4644016,0.4271026],"study_design_scores_gemma":[0.0000910831,0.0001931804,0.06735457,0.000946296,0.00003543191,0.00121824,0.006759594,0.0003120255,0.001236796,0.002983042,0.9187895,0.00008013196],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1173646,0.02119514,0.002371246,0.019507,0.001881644,0.0003459876,0.02012998,0.0005193611,0.816685],"genre_scores_gemma":[0.08182835,0.006220321,0.001460059,0.001523047,0.000200938,0.000122512,0.002688401,0.0002473735,0.905709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4721348,"threshold_uncertainty_score":0.7529356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1150414890899209,"score_gpt":0.2523988209804492,"score_spread":0.1373573318905283,"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."}}