{"id":"W6931690553","doi":"10.5683/sp3/m510ci","title":"Cape Duncan Ontario. 1:50,000. Map Sheet 043A10, ed. 1, 1994","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Cape; Natural (archaeology); Raster graphics; Aerial photography; Digital mapping; Topographic map (neuroanatomy); Orthophoto","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":[0.0004104314,0.002091449,0.001372354,0.003730386,0.001162738,0.002561747,0.002080766,0.0006544861,0.1581535],"category_scores_gemma":[0.002782966,0.0008673374,0.000605845,0.01498375,0.0004310269,0.0009834601,0.0009643835,0.001200991,0.170485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004479645,"about_ca_system_score_gemma":0.007870117,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6056597,"about_ca_topic_score_gemma":0.7657894,"domain_scores_codex":[0.9994437,0.00003608983,0.00003744184,0.0001659008,0.0002027374,0.0001140367],"domain_scores_gemma":[0.9985825,0.000157491,0.0001154399,0.0002343132,0.0007190039,0.0001912945],"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":[0.00001101443,0.000002956559,0.0003615477,0.0001152404,0.000005067435,0.000007896821,0.0000113205,0.00005808095,0.00002269939,0.000114694,0.997395,0.001894409],"study_design_scores_gemma":[0.00004153939,0.000002739122,0.005135078,0.000105965,0.000007924491,0.00001943222,0.00007352524,0.0001130354,0.00008978148,0.0002647281,0.9941347,0.00001168047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006300136,0.00004261767,0.00002850052,0.00002549537,0.00001110349,0.000003940245,0.997957,0.0001433105,0.001724955],"genre_scores_gemma":[0.0002923367,0.00009058329,0.0001685566,0.00001680814,0.000004188996,0.00002603152,0.9956812,0.00008509643,0.003635243],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3943403,"threshold_uncertainty_score":0.7933252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006677434833356559,"score_gpt":0.2403633695492869,"score_spread":0.2336859347159303,"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."}}