{"id":"W6912968368","doi":"10.5683/sp3/zkja5j","title":"Moose River Ontario. 1:50,000. Map Sheet 042I14, ed. 1, 1973","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; Aerial photography; Natural (archaeology); Topographic map (neuroanatomy); 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":[0.0003903042,0.001463047,0.001182351,0.004608682,0.001423005,0.002342066,0.001629008,0.0005083835,0.09178468],"category_scores_gemma":[0.002038213,0.0009021294,0.0006148061,0.01918171,0.0004227059,0.0008946076,0.001023115,0.0008557685,0.06593521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007530729,"about_ca_system_score_gemma":0.01375307,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.893128,"about_ca_topic_score_gemma":0.9411367,"domain_scores_codex":[0.9994346,0.00002593526,0.00004317281,0.0001288992,0.0002273962,0.0001398963],"domain_scores_gemma":[0.998596,0.00008270222,0.0001517649,0.0001673865,0.0008542098,0.000147861],"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":[0.00001887153,0.000004575362,0.001288065,0.0003019361,0.00001363877,0.00001639865,0.00005584782,0.00007866047,0.00004936587,0.0002586002,0.9944698,0.003444258],"study_design_scores_gemma":[0.00003255767,0.000002956579,0.01824694,0.0001485929,0.00001247483,0.00002394862,0.000158144,0.00007913171,0.000081112,0.0001807729,0.9810176,0.00001583205],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001162291,0.00005126638,0.0000206293,0.00002447741,0.00000847898,0.000005102238,0.9981992,0.00005661492,0.001518176],"genre_scores_gemma":[0.0007425649,0.0001362487,0.0001825075,0.00001729637,0.000004133557,0.00004227478,0.9945103,0.00006103636,0.004303628],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.106872,"threshold_uncertainty_score":0.3070503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01680337592104708,"score_gpt":0.2534682663174063,"score_spread":0.2366648903963592,"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."}}