{"id":"W6969496990","doi":"10.5683/sp3/te82vi","title":"Wigwasikak Lake Ontario. 1:50,000. Map Sheet 052N16, ed. 1, 1976","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; Natural (archaeology); Raster graphics; Topographic map (neuroanatomy); Aerial photography; Viewshed analysis; Geographic information system; Orthophoto","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":[0.0003901104,0.001944711,0.001310093,0.005248654,0.001602526,0.002944856,0.001746805,0.0005437044,0.1421058],"category_scores_gemma":[0.002314058,0.00106369,0.0005961876,0.02424769,0.0005217641,0.001189465,0.00111402,0.0009171842,0.1069885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01059611,"about_ca_system_score_gemma":0.01922052,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9212132,"about_ca_topic_score_gemma":0.9604462,"domain_scores_codex":[0.9993742,0.00002337254,0.00004921177,0.0001384456,0.0002630013,0.0001517407],"domain_scores_gemma":[0.9983969,0.00008321369,0.0001547651,0.0001854124,0.0009964197,0.0001833368],"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":[0.0000204478,0.000004009398,0.000961755,0.0003524077,0.000009814199,0.00001623606,0.00006425151,0.00008299671,0.00005356223,0.0002497563,0.9937795,0.004405321],"study_design_scores_gemma":[0.0000309381,0.000003008415,0.01194122,0.0001391697,0.000009420849,0.0000211125,0.000161141,0.00006625251,0.00008319681,0.0001478705,0.987382,0.00001466856],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001049096,0.00006210456,0.00002800038,0.00002608708,0.00001167485,0.000007170904,0.9971824,0.00009198167,0.002485632],"genre_scores_gemma":[0.0008216476,0.0001965744,0.0002245143,0.00001863771,0.000005355664,0.00005686953,0.9905917,0.0001055105,0.007979205],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1421058,"threshold_uncertainty_score":0.4753914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01736011448989114,"score_gpt":0.255086362103783,"score_spread":0.2377262476138919,"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."}}