{"id":"W7017791460","doi":"","title":"Canada VMap1, Library 37: Inundation Areas","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; Natural resource; Topographic map (neuroanatomy); Digital mapping; Natural (archaeology)","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":[],"consensus_categories":[],"category_scores_codex":[0.0003512022,0.0008787455,0.0005112845,0.005692116,0.003842148,0.003978739,0.001675433,0.0003442365,0.2386508],"category_scores_gemma":[0.002440478,0.0004896998,0.0003636901,0.02057026,0.0004467359,0.001194116,0.00122444,0.0005122692,0.06934226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02133838,"about_ca_system_score_gemma":0.06147538,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9765841,"about_ca_topic_score_gemma":0.982721,"domain_scores_codex":[0.9992903,0.00002207089,0.00002319296,0.00008313428,0.0004325782,0.0001485996],"domain_scores_gemma":[0.9980204,0.0000592321,0.00006187642,0.00009199332,0.001553346,0.00021316],"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":[0.00002814039,0.00001041287,0.001476252,0.0001516048,0.000004679538,0.00004624625,0.0003024661,0.0002501702,0.0001350382,0.003102863,0.951527,0.04296497],"study_design_scores_gemma":[0.000005580641,0.000002433008,0.007249375,0.00004588889,0.000003882541,0.00002722586,0.0002923273,0.0001850901,0.0002187834,0.0002986666,0.9916578,0.00001284495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003966477,0.0007111217,0.001478461,0.0004872182,0.0001525466,0.0002500866,0.5334889,0.00260558,0.4568597],"genre_scores_gemma":[0.03452163,0.002296487,0.007746023,0.0002488049,0.00006873449,0.00030497,0.3653125,0.002626564,0.5868743],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2386508,"threshold_uncertainty_score":0.7983665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01666545586286788,"score_gpt":0.2084719020364679,"score_spread":0.1918064461736,"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."}}