{"id":"W6950888283","doi":"10.5683/sp3/8m08ov","title":"Barthel Saskatchewan. 1:50,000. Map Sheet 073F14, ed. 1, 1969","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; Orthophoto; Natural (archaeology); Raster graphics; Government (linguistics); Topographic map (neuroanatomy); Viewshed analysis","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":[0.0004986454,0.002055005,0.00134638,0.004508795,0.001018359,0.003944393,0.001753476,0.0007551411,0.2811279],"category_scores_gemma":[0.002768725,0.001175237,0.0006670074,0.02424821,0.0004070396,0.001790204,0.001306356,0.001378624,0.3156263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005243593,"about_ca_system_score_gemma":0.01074087,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6718329,"about_ca_topic_score_gemma":0.7599235,"domain_scores_codex":[0.9993684,0.00004749872,0.00006130609,0.0001845588,0.0001938832,0.0001443645],"domain_scores_gemma":[0.9982471,0.0001448418,0.0001213539,0.0003124227,0.001002163,0.0001720326],"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":[0.00001626074,0.000002842787,0.0003352887,0.0001754155,0.00000990483,0.000009993907,0.00001594926,0.0000651333,0.00004238304,0.0002294549,0.9953908,0.00370652],"study_design_scores_gemma":[0.00002758945,0.000001986397,0.004863997,0.0001922189,0.000007391207,0.00001543729,0.00009451663,0.00005541809,0.0001025331,0.0003291472,0.9942929,0.00001706477],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004003759,0.00004087647,0.00002633307,0.00002185997,0.00001388438,0.000003249377,0.9976003,0.000116556,0.002137045],"genre_scores_gemma":[0.0004651167,0.0002009142,0.0002069366,0.00004353096,0.000005146798,0.00003675679,0.9892491,0.0001954699,0.009596962],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3281671,"threshold_uncertainty_score":0.9404666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326589965460924,"score_gpt":0.2544490872192963,"score_spread":0.2411831875646871,"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."}}