{"id":"W6913005701","doi":"10.5683/sp3/depqoc","title":"Chilko Mountain (East) British Columbia. 1:50,000. Map Sheet 092N01, ed. 1, 1968","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; Natural (archaeology); Aerial photography; Topographic map (neuroanatomy); Government (linguistics); Geographic information system","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":[0.0003105051,0.00176363,0.001139842,0.005073698,0.001745983,0.003751498,0.001563205,0.0005896313,0.1247021],"category_scores_gemma":[0.002041462,0.0008010276,0.0004725086,0.02267186,0.0003791971,0.001098774,0.0009784643,0.001282886,0.1020626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007133124,"about_ca_system_score_gemma":0.0139324,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9292639,"about_ca_topic_score_gemma":0.9646856,"domain_scores_codex":[0.9995229,0.00002036375,0.0000347406,0.0001255645,0.0001689076,0.0001274458],"domain_scores_gemma":[0.9983556,0.00007165459,0.000105617,0.0001684844,0.001124845,0.000173849],"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":[0.00001543473,0.000003089367,0.0006431641,0.0001695066,0.000007299095,0.00001245895,0.00002499267,0.0000501182,0.00002552734,0.0001511709,0.9955226,0.00337443],"study_design_scores_gemma":[0.00002516479,0.000002223615,0.01243537,0.0002295951,0.00001019079,0.00002202822,0.000183914,0.00008720027,0.00009997741,0.0001756701,0.9867094,0.00001908239],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001379869,0.0001024462,0.00002374045,0.00003226297,0.00001896241,0.000005975248,0.9959974,0.0001327997,0.003548497],"genre_scores_gemma":[0.001127505,0.0002423604,0.0001911131,0.00002928138,0.000006759032,0.00004259907,0.9871306,0.0001203757,0.01110947],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1247021,"threshold_uncertainty_score":0.41717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008839830296349,"score_gpt":0.2355506201428625,"score_spread":0.225462221839899,"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."}}