{"id":"W6931720018","doi":"10.5683/sp3/devn8b","title":"Lac Mistachagagane Quebec. 1:50,000. Map Sheet 022K16, ed. 1, 1967","year":2022,"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); Aerial photography; Geographic information system; Digital mapping; Viewshed analysis","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":[0.0005447213,0.002281581,0.001460389,0.005348603,0.001695863,0.003620001,0.002231524,0.000759343,0.1889162],"category_scores_gemma":[0.003128311,0.0008504093,0.0007615562,0.02389761,0.0004805314,0.001281892,0.0009906179,0.001390891,0.1160679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01287188,"about_ca_system_score_gemma":0.0186652,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9676592,"about_ca_topic_score_gemma":0.9798504,"domain_scores_codex":[0.9992562,0.00003948086,0.00004214637,0.000182247,0.0002812132,0.0001987076],"domain_scores_gemma":[0.9975728,0.0001331468,0.0001391864,0.0002837709,0.001648522,0.0002226702],"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":[0.00001924407,0.000004300616,0.0007051445,0.0001758016,0.000009806718,0.00001177937,0.00002405561,0.00009260985,0.00003476259,0.0002410553,0.9947336,0.003947896],"study_design_scores_gemma":[0.00003648934,0.000003385245,0.01039083,0.0002243857,0.000009567066,0.00002122286,0.0001170186,0.000157725,0.000100122,0.0002027479,0.9887139,0.00002254807],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007490376,0.00007388384,0.00003548198,0.00003054456,0.00001847505,0.00000642683,0.9970303,0.0001373022,0.002592659],"genre_scores_gemma":[0.001013339,0.0001829767,0.0002697421,0.00003274122,0.000007304739,0.0000478413,0.9886826,0.0001529255,0.009610461],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1889162,"threshold_uncertainty_score":0.6319876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01525196419949895,"score_gpt":0.2620756753721087,"score_spread":0.2468237111726098,"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."}}