{"id":"W6969376212","doi":"10.5683/sp3/cnzmz9","title":"Ottawa (West) Ontario. 1:50,000. Map Sheet 031G05, ed. 6, 1958","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; Government (linguistics); 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0009922568,0.001587127,0.001905087,0.0006885919,0.0003190977,0.0006207444,0.002552948,0.001595997,0.01466886],"category_scores_gemma":[0.0004260955,0.001773063,0.0007484882,0.0006127589,0.0003292825,0.0003679925,0.001015012,0.00230324,0.01347245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002314996,"about_ca_system_score_gemma":0.002341696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9597871,"about_ca_topic_score_gemma":0.9895583,"domain_scores_codex":[0.9921278,0.0005147524,0.001440524,0.002139048,0.001999859,0.001778056],"domain_scores_gemma":[0.9919176,0.0002364795,0.000947212,0.005605862,0.0004612728,0.0008315646],"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":[0.00007551406,0.0004401678,0.0001300462,0.0003011916,0.0005313928,0.001700852,0.0001051864,0.00001336202,0.00001624421,0.00004568207,0.9964731,0.0001672587],"study_design_scores_gemma":[0.0009338128,0.0001019252,0.004876906,0.0004678516,0.0008620099,0.0001569068,0.00005437633,0.000001673144,0.00002831545,0.00007588034,0.9905161,0.001924246],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001226279,0.001369065,0.000002151866,0.0002810324,0.001397604,0.0008160833,0.988965,0.0004260243,0.006730719],"genre_scores_gemma":[0.00000164651,0.000250967,0.0004663945,0.001162925,0.001972835,0.0003046536,0.9923129,0.000510703,0.003016992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02977131,"threshold_uncertainty_score":0.9999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01701792397847754,"score_gpt":0.2600346747489058,"score_spread":0.2430167507704283,"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."}}