{"id":"W6894337204","doi":"10.5683/sp3/qyyrhh","title":"Lac Opataouaga Quebec. 1:50,000. Map Sheet 032K07, ed. 1, 1976","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; Raster graphics; General partnership; Natural (archaeology); Geographic information system; Aerial photography; Viewshed analysis; Digital mapping","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":[0.0005229548,0.002098473,0.001447185,0.005757838,0.001653458,0.003329343,0.002263052,0.0007439737,0.1599528],"category_scores_gemma":[0.002894699,0.0008092055,0.0007127217,0.02628359,0.0004584602,0.001138695,0.0008743006,0.001313447,0.09816393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01491266,"about_ca_system_score_gemma":0.02200237,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9742182,"about_ca_topic_score_gemma":0.9829107,"domain_scores_codex":[0.9992914,0.00003507113,0.00004166786,0.0001592033,0.0002745187,0.0001981492],"domain_scores_gemma":[0.9974705,0.0001282228,0.0001391171,0.0002522959,0.001784829,0.0002250786],"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":[0.00001664775,0.000005110875,0.0007963347,0.0001657049,0.000009741471,0.00001121487,0.0000234129,0.0001005009,0.00003194901,0.0002456335,0.9943886,0.004204976],"study_design_scores_gemma":[0.0000416391,0.000003916919,0.01495721,0.0002381248,0.00001148127,0.00002231228,0.0001412943,0.0002096572,0.0001128103,0.000220449,0.9840165,0.00002452351],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008752986,0.00007315381,0.0000323015,0.00003099347,0.00001651651,0.000007209708,0.9972906,0.0001180486,0.00234359],"genre_scores_gemma":[0.001122337,0.0001980096,0.0002707064,0.00003317402,0.000007119645,0.00005603641,0.9893653,0.0001266773,0.008820715],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1599528,"threshold_uncertainty_score":0.5350955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692699519490289,"score_gpt":0.2668512569630283,"score_spread":0.2499242617681254,"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."}}