{"id":"W6931878091","doi":"10.5683/sp3/jrshyx","title":"St. Thomas Ontario. 1:50,000. Map Sheet 040I14, ed. 4, 1975","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Natural (archaeology); Government (linguistics); Aerial photography; Digital mapping; 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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007089361,0.0005073192,0.0006586117,0.0002845698,0.0003400567,0.001377932,0.002568928,0.0003776666,0.0006112524],"category_scores_gemma":[0.0001557088,0.0004797413,0.0002113627,0.0002936867,0.00006526367,0.0009192818,0.00113113,0.0006465844,0.0001143248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001862627,"about_ca_system_score_gemma":0.0008784317,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05035133,"about_ca_topic_score_gemma":0.04083896,"domain_scores_codex":[0.9967742,0.00006370535,0.0009970809,0.0006556596,0.00092029,0.0005890676],"domain_scores_gemma":[0.9963639,0.000122736,0.0008124931,0.002118844,0.0003449327,0.000237107],"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":[0.000001315463,0.00006238606,0.000003734309,0.0004637949,0.000040005,0.0000375304,0.0006566331,0.0000219225,2.36126e-7,0.001526045,0.9951942,0.001992201],"study_design_scores_gemma":[0.0001926087,0.00003308489,0.00003740675,0.0004206147,0.00003507088,0.00005411271,0.00003268698,0.002220589,0.00001303553,0.002079807,0.994309,0.0005719488],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001262823,0.0005346848,0.06243476,0.0002391371,0.001130796,0.0002190812,0.9267811,0.0002195097,0.008439719],"genre_scores_gemma":[0.000001194036,0.0001121083,0.02484652,0.001645166,0.0004425049,0.00002528085,0.9716082,0.00002070401,0.00129828],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0448272,"threshold_uncertainty_score":0.9997655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764928876499475,"score_gpt":0.2474460218425193,"score_spread":0.2297967330775245,"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."}}