{"id":"W6950448176","doi":"10.5683/sp3/8pnaem","title":"Lac Saint Henri Quebec. 1:50,000. Map Sheet 021M12, ed. 1, 1962","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; SAINT; General partnership; Raster graphics; Natural (archaeology); Government (linguistics); Aerial photography; Geographic information system","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":[0.0006398862,0.002350314,0.001508054,0.005777137,0.001708236,0.003690196,0.002413583,0.0007900643,0.1770205],"category_scores_gemma":[0.003437831,0.0008564435,0.0008187419,0.02261154,0.0005001726,0.001332113,0.001021207,0.001449667,0.1113393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01299711,"about_ca_system_score_gemma":0.01961136,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9645823,"about_ca_topic_score_gemma":0.9778001,"domain_scores_codex":[0.999167,0.00004733591,0.00004527921,0.0002085248,0.0003147322,0.0002171887],"domain_scores_gemma":[0.9975296,0.0001399209,0.0001366055,0.0002934954,0.001675786,0.0002246484],"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":[0.00001619496,0.000004465308,0.0006475453,0.0001656411,0.000009723086,0.00001107039,0.0000236617,0.00008943027,0.00003264624,0.0002543308,0.994958,0.003787361],"study_design_scores_gemma":[0.0000363414,0.000003226522,0.009598747,0.0002190567,0.000009320114,0.00002149441,0.00009997492,0.0001556382,0.00009223605,0.0002109748,0.9895307,0.00002217934],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007748573,0.00008323461,0.00003698899,0.00003400736,0.00001975271,0.000007238521,0.9971956,0.0001481696,0.002397484],"genre_scores_gemma":[0.001020741,0.000178253,0.0002993104,0.00003785819,0.000008909675,0.00005088657,0.9898999,0.0001733525,0.008330802],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1770205,"threshold_uncertainty_score":0.5921926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01477116600785832,"score_gpt":0.2624679029775613,"score_spread":0.247696736969703,"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."}}