{"id":"W6989777049","doi":"","title":"Canada VMap1, Library 21: Trails and Tracks 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; Topographic map (neuroanatomy); Natural (archaeology); 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":[0.0005954618,0.00104184,0.0006098523,0.006139247,0.005928371,0.006420919,0.002322378,0.0006521011,0.3607054],"category_scores_gemma":[0.004147425,0.000746247,0.0004765354,0.02281968,0.0007953244,0.001945225,0.001648633,0.0008457751,0.1575325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0220322,"about_ca_system_score_gemma":0.08077402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9649212,"about_ca_topic_score_gemma":0.9770518,"domain_scores_codex":[0.9985805,0.00004955084,0.00004765311,0.0001471208,0.000926033,0.0002492745],"domain_scores_gemma":[0.9959266,0.0001081767,0.0001097248,0.0002620111,0.003097514,0.0004959887],"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":[0.00003150379,0.00001299627,0.0006752826,0.0001077925,0.000003442085,0.00003140642,0.0002102685,0.000262346,0.0001161052,0.003847314,0.9580414,0.03666009],"study_design_scores_gemma":[0.000005277992,0.000002598463,0.002369126,0.0000358923,0.000002573245,0.00001803775,0.000163262,0.0001358478,0.0001337907,0.0003194628,0.9968022,0.00001189691],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.002200154,0.0004035038,0.002925472,0.0005053707,0.0002458033,0.0003680204,0.3927773,0.004371667,0.5962027],"genre_scores_gemma":[0.01386983,0.001020693,0.009609108,0.0002038073,0.00005803133,0.0002512657,0.2558339,0.002820916,0.7163324],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.3607054,"threshold_uncertainty_score":0.9118762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01722478898587361,"score_gpt":0.2089599098220657,"score_spread":0.1917351208361921,"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."}}