{"id":"W6894204085","doi":"10.5683/sp3/vcgpsq","title":"Key Harbour Ontario. 1:50,000. Map Sheet 041H15, ed. 4, 1977","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; Key (lock); Raster graphics; Natural (archaeology); Aerial photography; Harbour; Government (linguistics)","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":[0.0004068802,0.001723629,0.001202667,0.005064799,0.001504118,0.002748401,0.001732336,0.0005616616,0.1509375],"category_scores_gemma":[0.002538909,0.0009642044,0.0006745182,0.01971569,0.0005255916,0.001093358,0.001108707,0.0008728306,0.1179534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009746955,"about_ca_system_score_gemma":0.0173525,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9097497,"about_ca_topic_score_gemma":0.9514328,"domain_scores_codex":[0.9993401,0.00002855756,0.00005181882,0.0001473931,0.0002703975,0.000161708],"domain_scores_gemma":[0.9981278,0.0001088473,0.0001693738,0.0002046679,0.001179764,0.0002096916],"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":[0.00001556793,0.000003147276,0.0007767645,0.0002721378,0.000009110951,0.0000117808,0.00003696279,0.00006638363,0.00003784164,0.0001946232,0.9958544,0.00272131],"study_design_scores_gemma":[0.00003308394,0.000002907051,0.01201481,0.0001394212,0.00001001852,0.00001849975,0.0001316032,0.00007001451,0.00008252802,0.0001638066,0.9873188,0.00001463811],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007307228,0.00005212676,0.00002063645,0.00002496604,0.00001198934,0.000005439177,0.9978839,0.00007080719,0.001857195],"genre_scores_gemma":[0.0006628611,0.0001576541,0.0001720211,0.00002257183,0.000007029535,0.00004171296,0.9926523,0.00008569822,0.006198079],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1509375,"threshold_uncertainty_score":0.5049363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01758045228631357,"score_gpt":0.254241907268096,"score_spread":0.2366614549817825,"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."}}