{"id":"W3010545137","doi":"10.1007/s11759-020-09392-w","title":"“Raging Against the Machine: Archaeology, Metal Detection and Municipal Legislation in Ontario, Canada”","year":2020,"lang":"en","type":"article","venue":"Archaeologies","topic":"Cultural Heritage Management and Preservation","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Legislation; Archaeology; Disadvantage; Power (physics); Political science; Law; Public administration; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001327223,0.0002787123,0.0003455121,0.002123968,0.0209744,0.004802767,0.002080451,0.001568452,0.007605149],"category_scores_gemma":[0.005479303,0.0006540066,0.0004307757,0.007244788,0.007084004,0.001781542,0.003034472,0.00182465,0.0004308618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1354976,"about_ca_system_score_gemma":0.2474544,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9993715,"about_ca_topic_score_gemma":0.9998847,"domain_scores_codex":[0.9978459,0.0002023674,0.00008995453,0.0001741564,0.0007241769,0.0009634808],"domain_scores_gemma":[0.9954093,0.0005581437,0.0005476124,0.0001409083,0.002289721,0.001054271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003485598,0.0001557118,0.4295661,0.0007648935,0.00009601213,0.002434759,0.3157533,0.0007910429,0.00175348,0.03398076,0.1093458,0.1050095],"study_design_scores_gemma":[0.00001088878,0.00003140346,0.5737747,0.0003756174,0.00004027122,0.0002724039,0.2603716,0.0002933693,0.00035707,0.0007620219,0.1636448,0.00006592187],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8830631,0.006710059,0.0006471023,0.03298558,0.0001982844,0.0001440032,0.002515575,0.00005089385,0.07368541],"genre_scores_gemma":[0.9369643,0.004132789,0.000945794,0.002457295,0.00003007728,0.00004466969,0.0006446128,0.00005126571,0.0547291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1354976,"threshold_uncertainty_score":0.9831083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.079984644197024,"score_gpt":0.214617938053339,"score_spread":0.134633293856315,"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."}}