{"id":"W6980417817","doi":"","title":"Canada VMap1, Library 36: Depth 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; Topographic map (neuroanatomy); Base (topology); Natural (archaeology); 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005538041,0.00112002,0.0005700252,0.005783031,0.004463112,0.005863779,0.002246781,0.000633022,0.4846042],"category_scores_gemma":[0.004564616,0.0007822545,0.0005003065,0.01816808,0.0006893661,0.00246229,0.001644791,0.0008327882,0.2658283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02107697,"about_ca_system_score_gemma":0.05655602,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9383575,"about_ca_topic_score_gemma":0.9513756,"domain_scores_codex":[0.9986457,0.00003880259,0.00004591595,0.000151888,0.0008908384,0.0002267915],"domain_scores_gemma":[0.9955217,0.0001108138,0.00008085385,0.0002758192,0.003605363,0.0004054672],"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":[0.00002346591,0.000008260864,0.0003582977,0.00008067474,0.000001866518,0.00002078564,0.0001429565,0.0001336949,0.0001274882,0.002685341,0.9654437,0.03097348],"study_design_scores_gemma":[0.000004556756,0.000001714278,0.001221862,0.00002620707,0.000001631769,0.00001548477,0.00009778771,0.00008098842,0.0001824262,0.0002621861,0.9980957,0.000009546231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.001428638,0.000383051,0.002727808,0.0006067377,0.0002179204,0.0002657445,0.3426064,0.007105935,0.6446577],"genre_scores_gemma":[0.009173049,0.0009000461,0.007294696,0.0002977699,0.00006863007,0.0002076625,0.1694264,0.004742404,0.8078892],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.4846042,"threshold_uncertainty_score":0.7351495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.020346066261034,"score_gpt":0.2169698868969982,"score_spread":0.1966238206359642,"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."}}