{"id":"W6894410968","doi":"10.5683/sp3/pzrkzx","title":"Ridgetown (West) Ontario. 1:50,000. Map Sheet 040I05, ed. 4, 1962","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); Digital mapping; Aerial photography; Government (linguistics); Viewshed analysis; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0009316577,0.001773491,0.001988283,0.0006949955,0.0003626721,0.0006862654,0.002616891,0.001612102,0.01776023],"category_scores_gemma":[0.0004251791,0.001839389,0.0007916343,0.0006079935,0.0003625442,0.0003722104,0.001209635,0.002460181,0.01339754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003706664,"about_ca_system_score_gemma":0.004359214,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.942414,"about_ca_topic_score_gemma":0.9734367,"domain_scores_codex":[0.9919338,0.0005002293,0.001390379,0.002245526,0.002076402,0.001853611],"domain_scores_gemma":[0.9917528,0.0002341389,0.0009192682,0.005718755,0.0004957374,0.0008792778],"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":[0.0001145752,0.0004924444,0.0001072901,0.0002899912,0.0005535618,0.001834556,0.0001839979,0.00001904004,0.00001737469,0.00002929873,0.9962228,0.0001350878],"study_design_scores_gemma":[0.0009264477,0.0001115749,0.003887273,0.0004919561,0.00094452,0.0001723101,0.00005129881,0.000002385162,0.00004244323,0.00006485231,0.9912845,0.002020372],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001861703,0.001607508,0.000002630992,0.0002771796,0.00155132,0.0008571013,0.9899976,0.0004408039,0.005247196],"genre_scores_gemma":[0.000001775167,0.0003210223,0.0003893299,0.001135611,0.002226753,0.0003285237,0.9901125,0.0005062826,0.004978186],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03102269,"threshold_uncertainty_score":0.9998412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846528955440387,"score_gpt":0.2604818896850961,"score_spread":0.2420166001306922,"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."}}