{"id":"W6969588841","doi":"10.5683/sp3/csjhuq","title":"Port Hope Ontario. 1:50,000. Map Sheet 030M16, ed. 3, 1973","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; Port (circuit theory); General partnership; Raster graphics; Government (linguistics); Natural (archaeology); Aerial photography; Topographic map (neuroanatomy); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004954498,0.002029555,0.001324399,0.005136757,0.001400182,0.003051057,0.00201598,0.0006576452,0.16824],"category_scores_gemma":[0.003274545,0.001076795,0.0007633494,0.02136285,0.0005369746,0.001429202,0.001218805,0.001105032,0.1478556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008457134,"about_ca_system_score_gemma":0.01483814,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8568495,"about_ca_topic_score_gemma":0.9127321,"domain_scores_codex":[0.9992686,0.0000365616,0.00005703322,0.0001678101,0.000305337,0.0001646683],"domain_scores_gemma":[0.9979761,0.0001435433,0.0001766469,0.0002668507,0.00121395,0.0002228987],"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":[0.00001243316,0.000002607579,0.0004133994,0.0002511121,0.000006696974,0.000009903114,0.00002611543,0.0000523258,0.00003006779,0.0001892454,0.9968578,0.002148303],"study_design_scores_gemma":[0.00002788034,0.000002294233,0.005903533,0.000141198,0.00000796251,0.00001755585,0.0000853858,0.00006182251,0.00007243081,0.000179482,0.993487,0.00001345768],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004065592,0.0000457214,0.00002317503,0.00002336856,0.00001081826,0.000004518828,0.9979877,0.0001021712,0.001761709],"genre_scores_gemma":[0.0003966353,0.0001403232,0.0001806834,0.00002099532,0.000006042524,0.00003598546,0.9944884,0.0001148792,0.004616114],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.16824,"threshold_uncertainty_score":0.5628189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767222695344195,"score_gpt":0.2589687204584457,"score_spread":0.2412964935050038,"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."}}