{"id":"W7027013351","doi":"","title":"Canada VMap1, Library 44: Landmark 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; Landmark; Geographic information system; Digital mapping; Topographic map (neuroanatomy); National library","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":[0.0006881649,0.00104445,0.0005927396,0.006613745,0.006053788,0.006959174,0.002328208,0.0007582895,0.4677475],"category_scores_gemma":[0.005639758,0.0007009028,0.0004447923,0.02227138,0.000932027,0.00213609,0.001746469,0.001003278,0.2600701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02452562,"about_ca_system_score_gemma":0.08176702,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.951076,"about_ca_topic_score_gemma":0.960856,"domain_scores_codex":[0.9983713,0.0000581935,0.00005424531,0.0001870434,0.001059802,0.0002693672],"domain_scores_gemma":[0.9943785,0.0001466572,0.000116358,0.0003605917,0.004457974,0.000539861],"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":[0.00002123246,0.000007418929,0.0002944519,0.00006408721,0.000001556045,0.00002075203,0.0001409343,0.0001090958,0.00008412359,0.003684658,0.9694672,0.02610455],"study_design_scores_gemma":[0.000003461827,0.000001739209,0.001021052,0.00002312784,0.000001239104,0.00001286767,0.0000964758,0.00005836566,0.0001179417,0.0002262211,0.998429,0.000008405115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.001496175,0.0004137679,0.002408597,0.0007888807,0.0003074835,0.0003036188,0.2737362,0.00507717,0.7154682],"genre_scores_gemma":[0.007925013,0.0008282298,0.005967589,0.0002394918,0.00006692606,0.0002143935,0.1568573,0.003198683,0.8247024],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.4677475,"threshold_uncertainty_score":0.7591935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668120855222916,"score_gpt":0.2088456869126362,"score_spread":0.192164478360407,"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."}}