{"id":"W6989744395","doi":"","title":"Canada VMap1, Library 20: Track Lines","year":2016,"lang":"en","type":"other","venue":"The Faculty Digital Archive (New York University)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scale (ratio); Product (mathematics); Vector map; Geographic information system; Digital mapping; Base (topology); Track (disk drive); Topographic map (neuroanatomy)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001083542,0.001279041,0.0007405413,0.00610673,0.006140918,0.009194206,0.003134918,0.001119024,0.612842],"category_scores_gemma":[0.007322449,0.0009303706,0.0005612725,0.01727171,0.0009004968,0.002801641,0.00198761,0.001083587,0.463692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02156801,"about_ca_system_score_gemma":0.07794344,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9078088,"about_ca_topic_score_gemma":0.92014,"domain_scores_codex":[0.9978746,0.00007449305,0.00007419039,0.0002632822,0.001370564,0.0003427161],"domain_scores_gemma":[0.9905008,0.0002123947,0.0001569543,0.0006793845,0.007454101,0.000996433],"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":[0.00002187654,0.00001081006,0.0002172915,0.00005523757,0.000001669095,0.0000142239,0.00006103156,0.00007596652,0.00008372846,0.002248285,0.9766574,0.02055256],"study_design_scores_gemma":[0.00000540678,0.000002698413,0.0007007231,0.00002136886,0.00000142083,0.00001112707,0.00005321263,0.00007466984,0.0001409906,0.000213529,0.9987673,0.000007655165],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0009508561,0.0002884223,0.002684972,0.0007710048,0.0004406976,0.0003694837,0.2207861,0.007508675,0.7661998],"genre_scores_gemma":[0.00329187,0.0004405593,0.003423462,0.0002323647,0.00006301982,0.0001689427,0.1165146,0.003121521,0.8727436],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.612842,"threshold_uncertainty_score":0.5522338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01867684653588967,"score_gpt":0.2125849699012265,"score_spread":0.1939081233653369,"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."}}