{"id":"W6980413303","doi":"","title":"Canada VMap1, Library 16: Bridge 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); Bridge (graph theory); Vector map; Geographic information system; Base (topology)","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":[0.000687028,0.001077999,0.0006215533,0.005243453,0.005458798,0.006867247,0.002635154,0.0008939587,0.5623472],"category_scores_gemma":[0.004934175,0.0007595566,0.0004705422,0.01746617,0.0007831275,0.002538724,0.00180111,0.000938547,0.3195813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01810381,"about_ca_system_score_gemma":0.06180134,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9182396,"about_ca_topic_score_gemma":0.9401625,"domain_scores_codex":[0.9984823,0.00005121905,0.00004634812,0.0001718109,0.0009990437,0.0002494315],"domain_scores_gemma":[0.9954042,0.0001275601,0.00008684345,0.0003553119,0.003525917,0.0005000867],"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":[0.00002139524,0.00001036014,0.0002903591,0.00006421004,0.000001648287,0.00002172215,0.0001168477,0.0001067429,0.0001091056,0.003260563,0.9639512,0.03204575],"study_design_scores_gemma":[0.000004216193,0.000002113871,0.000834603,0.00002363971,0.000001338286,0.00001464807,0.00008623905,0.00008020942,0.0001327669,0.0002748794,0.9985378,0.000007712535],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.001401548,0.0003587414,0.002573704,0.0006151253,0.0002245105,0.000237396,0.168826,0.005971599,0.8197915],"genre_scores_gemma":[0.006183577,0.0006523856,0.0043902,0.0002298309,0.00004921847,0.0001497722,0.1041288,0.003349193,0.8808669],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.5623472,"threshold_uncertainty_score":0.6242586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02278702188531145,"score_gpt":0.2187227654648849,"score_spread":0.1959357435795735,"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."}}