{"id":"W6931950057","doi":"10.5683/sp3/32fhiq","title":"Harcourt (East) New Brunswick. 1:50,000. Map Sheet 021I06, ed. 1, 1955","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Orthophoto; Natural (archaeology); Viewshed analysis; Government (linguistics); Digital mapping","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":[0.0006478121,0.002048413,0.001337577,0.005418986,0.001082303,0.004006146,0.002113621,0.0005944105,0.235863],"category_scores_gemma":[0.003592518,0.001111764,0.0006201119,0.02533947,0.0004090132,0.001803077,0.001327389,0.001359695,0.2327724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006266722,"about_ca_system_score_gemma":0.01086986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7420424,"about_ca_topic_score_gemma":0.8338103,"domain_scores_codex":[0.9991085,0.00004792512,0.00009427289,0.0002470389,0.0003040755,0.0001981794],"domain_scores_gemma":[0.9977241,0.0001562699,0.0002010873,0.000390765,0.001346995,0.000180716],"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":[0.00001719424,0.000003435202,0.0005384968,0.0002275034,0.000008547148,0.00001419007,0.0000281973,0.00007816531,0.00005122194,0.0003068312,0.9930676,0.00565863],"study_design_scores_gemma":[0.00001736999,0.000001644618,0.004538184,0.0001437932,0.000004156055,0.00001417616,0.00009389482,0.0000328536,0.00007691346,0.0001677903,0.9948968,0.00001242362],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005866991,0.00008318151,0.0000416386,0.000027517,0.00002569643,0.000006133522,0.9961091,0.0001495547,0.003498576],"genre_scores_gemma":[0.000575671,0.0002250505,0.0002633175,0.0000335168,0.00000663538,0.00003692221,0.9877544,0.0002232514,0.01088136],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2579576,"threshold_uncertainty_score":0.7890404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01896258733705542,"score_gpt":0.2635351095342115,"score_spread":0.2445725221971561,"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."}}