{"id":"W6931786705","doi":"10.5683/sp3/f4smws","title":"Fawnie Creek British Columbia. 1:50,000. Map Sheet 093F03, 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; Raster graphics; Natural (archaeology); Topographic map (neuroanatomy); Aerial photography; 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":[0.0003748076,0.001763816,0.001252101,0.005497045,0.001790218,0.003589059,0.001672056,0.00065686,0.1594604],"category_scores_gemma":[0.002588765,0.0008784181,0.0005334399,0.02587367,0.0004154429,0.001146887,0.0009499007,0.00124431,0.1266343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007931703,"about_ca_system_score_gemma":0.01503994,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9198204,"about_ca_topic_score_gemma":0.9524648,"domain_scores_codex":[0.9994009,0.00002550335,0.00004544279,0.0001507205,0.0002288537,0.0001486316],"domain_scores_gemma":[0.998118,0.0001000165,0.0001080009,0.0002047974,0.001292827,0.0001763078],"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":[0.00001310666,0.000003016714,0.000452885,0.0001573232,0.000005635648,0.00001043892,0.00001924406,0.00005056064,0.0000251094,0.0001528345,0.9958408,0.003268969],"study_design_scores_gemma":[0.00002341927,0.000002069934,0.008517197,0.0001907577,0.000007955879,0.00001969426,0.0001238001,0.0000791249,0.00009155412,0.0001938763,0.9907334,0.00001711163],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007951209,0.00006357898,0.00002274571,0.00002411228,0.00001610336,0.000004836568,0.9970626,0.0001031267,0.002623463],"genre_scores_gemma":[0.0007060946,0.000179622,0.0001942879,0.00002450915,0.000004996519,0.00003772633,0.9896795,0.0001120594,0.009061231],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1594604,"threshold_uncertainty_score":0.5334482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307146025990639,"score_gpt":0.2432192697313484,"score_spread":0.230147809471442,"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."}}