{"id":"W6931603829","doi":"10.5683/sp3/uvgvbl","title":"Big Sandy Lake Saskatchewan. 1:50,000. Map Sheet 073I08, ed. 1, 1973","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; Natural (archaeology); Raster graphics; Government (linguistics); Aerial photography; Topographic map (neuroanatomy); 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":[0.0004448103,0.002188671,0.001240174,0.004342732,0.001019356,0.003081532,0.001939763,0.0007966958,0.1728159],"category_scores_gemma":[0.002323673,0.001149248,0.0007490916,0.02547465,0.0004331473,0.001466697,0.001327706,0.001360283,0.1796354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006052652,"about_ca_system_score_gemma":0.01479696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7549778,"about_ca_topic_score_gemma":0.8446518,"domain_scores_codex":[0.9994482,0.00004003952,0.00005751588,0.000134909,0.000160055,0.0001593053],"domain_scores_gemma":[0.9981889,0.0001213741,0.0001167248,0.0002594852,0.001142855,0.0001706961],"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":[0.00001656649,0.00000371503,0.0006428654,0.0001925223,0.00001188321,0.00001227017,0.00002114449,0.0000805556,0.00004182052,0.00016344,0.9962614,0.002551739],"study_design_scores_gemma":[0.00006527107,0.000003559391,0.01183807,0.0002526335,0.00001321758,0.00002001031,0.0002409119,0.0001060203,0.0001465449,0.0003799292,0.9869053,0.00002845156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005513503,0.00002370878,0.00001599568,0.00001754146,0.00001129999,0.000003804288,0.9987437,0.0000662042,0.001062771],"genre_scores_gemma":[0.0004587229,0.000104388,0.0001356555,0.00003064615,0.000003100294,0.00004645511,0.9950076,0.0000829877,0.004130328],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2450222,"threshold_uncertainty_score":0.5781269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01776271436081197,"score_gpt":0.2566498242736687,"score_spread":0.2388871099128567,"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."}}