{"id":"W6950489760","doi":"10.5683/sp3/khuxx8","title":"Noganosh Lake (East) Ontario. 1:50,000. Map Sheet 041H16, ed. 1, 1965","year":2021,"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); Viewshed analysis; Digital mapping","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0007656639,0.001730098,0.001891111,0.0006847717,0.0003513308,0.0006342481,0.002490164,0.001636739,0.02278897],"category_scores_gemma":[0.0003668685,0.00183314,0.0007852571,0.0006359508,0.0003257855,0.0003481371,0.00117728,0.002375195,0.009891826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001172294,"about_ca_system_score_gemma":0.002477553,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8141012,"about_ca_topic_score_gemma":0.9953086,"domain_scores_codex":[0.9920955,0.0004633939,0.001282833,0.002187517,0.002171417,0.00179937],"domain_scores_gemma":[0.9922726,0.0001590615,0.0008855676,0.005299025,0.0005348125,0.0008489844],"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":[0.0001442755,0.0004895712,0.0001344912,0.0002691743,0.0007062478,0.001944179,0.0001283247,0.00001375467,0.00001899903,0.00002941685,0.9960121,0.0001094447],"study_design_scores_gemma":[0.001111855,0.0001001047,0.001701444,0.0004004254,0.000883596,0.0001699493,0.00006052986,0.000001740816,0.00002201884,0.00004632185,0.9935793,0.001922724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001049116,0.001059256,0.000002340733,0.0002397354,0.001613413,0.0008345753,0.9904249,0.0004202572,0.005395006],"genre_scores_gemma":[6.916716e-7,0.0002182141,0.0004178985,0.001212922,0.002176588,0.0002787618,0.9898386,0.000505825,0.005350481],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1812074,"threshold_uncertainty_score":0.9999264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699051124322773,"score_gpt":0.2475225563417057,"score_spread":0.230532045098478,"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."}}