{"id":"W6969579279","doi":"10.5683/sp3/pjc6el","title":"Big Berry Mountains (East) Quebec. 1:50,000. Map Sheet 022B09, ed. 1, 1958","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; Natural (archaeology); Government (linguistics); Raster graphics; Viewshed analysis; Digital mapping; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001412542,0.001805668,0.001850709,0.001601706,0.0007882408,0.0005500656,0.00399591,0.001108901,0.05013393],"category_scores_gemma":[0.0003953025,0.002096963,0.0008171728,0.00116032,0.0005140191,0.0004003297,0.002358319,0.002600468,0.004289859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003236862,"about_ca_system_score_gemma":0.001566328,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8846437,"about_ca_topic_score_gemma":0.8184212,"domain_scores_codex":[0.9899933,0.0009715896,0.001515568,0.00235587,0.003020518,0.002143123],"domain_scores_gemma":[0.9917454,0.0002494918,0.001243311,0.005624578,0.0002638929,0.0008733366],"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":[0.0002950404,0.0006134408,0.00002156144,0.0003856576,0.000579152,0.0008686215,0.0001419475,0.00008236724,0.00002062179,0.0002178415,0.9957371,0.001036593],"study_design_scores_gemma":[0.001113176,0.0001746242,0.0009316104,0.0001307977,0.0008343902,0.000119536,0.0003395395,0.00001133208,0.000005561094,0.0001378886,0.9940234,0.002178175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001249756,0.001816221,0.000002573704,0.0005261315,0.001883511,0.001368429,0.9912201,0.0008236593,0.002346877],"genre_scores_gemma":[0.000003911407,0.0005448138,0.0000721058,0.001558452,0.002714072,0.001126248,0.9904346,0.0008224802,0.002723256],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06622253,"threshold_uncertainty_score":0.9997005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02019136593496074,"score_gpt":0.2625476739063922,"score_spread":0.2423563079714315,"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."}}