{"id":"W6989820755","doi":"","title":"Canada VMap1, Library 16: Runway Points","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); Runway; Vector map; Geographic information system; Base (topology); Topographic map (neuroanatomy); Natural resource","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":[0.0004369796,0.001184935,0.0006846497,0.005401,0.003695926,0.004731117,0.002310824,0.0005492056,0.3071889],"category_scores_gemma":[0.002872825,0.0006675645,0.0005462453,0.02164116,0.0005551629,0.001603928,0.00156541,0.0007648731,0.1374504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01388164,"about_ca_system_score_gemma":0.04879168,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9532405,"about_ca_topic_score_gemma":0.9663184,"domain_scores_codex":[0.9988476,0.0000350892,0.00003478686,0.0001453618,0.000743617,0.0001935066],"domain_scores_gemma":[0.9978346,0.00005696039,0.00006178761,0.0001469085,0.00167799,0.0002217158],"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":[0.00004237355,0.0000110044,0.001175227,0.0001486134,0.000005506332,0.0000375157,0.0002153348,0.000397994,0.00014792,0.003555532,0.9479635,0.04629936],"study_design_scores_gemma":[0.000007978815,0.00000302253,0.003831479,0.00005539372,0.000004259675,0.0000254464,0.0001611589,0.0002537555,0.000216047,0.0004374672,0.994988,0.00001598893],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002585302,0.0005994086,0.003618938,0.0003328149,0.0001628733,0.0002365772,0.517546,0.005017447,0.4699006],"genre_scores_gemma":[0.02215989,0.001651277,0.01398972,0.0001541569,0.00007830031,0.000317889,0.4140776,0.003763388,0.5438077],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3071889,"threshold_uncertainty_score":0.9882109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588212537379289,"score_gpt":0.2055407239963855,"score_spread":0.1896585986225926,"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."}}