{"id":"W6969644314","doi":"10.5683/sp3/rvhgle","title":"Sunshine (West) Ontario. 1:50,000. Map Sheet 052A12, ed. 1, 1959","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; Viewshed analysis; Digital mapping; Natural (archaeology); Geographic information system; Orthophoto; Aerial photography","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":[0.0003736355,0.00164494,0.001174116,0.0041298,0.001601364,0.003077075,0.00145935,0.0005633429,0.1585222],"category_scores_gemma":[0.002357322,0.0008825248,0.0006643539,0.0178463,0.0005244536,0.001094683,0.001031756,0.0009077179,0.1156021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009438955,"about_ca_system_score_gemma":0.0157061,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.917287,"about_ca_topic_score_gemma":0.9593779,"domain_scores_codex":[0.9994082,0.00002424267,0.00004492068,0.0001497467,0.0002255343,0.0001472737],"domain_scores_gemma":[0.998355,0.00008280173,0.0001423823,0.000194474,0.001044361,0.0001810099],"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":[0.00002134175,0.000002972185,0.0008569168,0.0002904634,0.000008790461,0.00001334923,0.00004683051,0.00005879192,0.00004191239,0.0002457748,0.9952586,0.003154149],"study_design_scores_gemma":[0.00002989828,0.000002423825,0.01090278,0.0001428704,0.000008317384,0.00001830466,0.0001189037,0.00004451803,0.00007151339,0.0001314243,0.9885174,0.00001156994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000812224,0.00007989272,0.00002432857,0.00002939302,0.00001626069,0.000005608563,0.9968162,0.0000979447,0.002849185],"genre_scores_gemma":[0.0009913027,0.0002281832,0.0002118789,0.00002974859,0.000008603671,0.0000380752,0.9891369,0.0001223683,0.009232972],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1585222,"threshold_uncertainty_score":0.5303095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035263124953023,"score_gpt":0.2646441124432151,"score_spread":0.2442914811936849,"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."}}