{"id":"W6999065664","doi":"","title":"Canada VMap1, Library 17: Buildings 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); Vector map; Geographic information system; Base (topology); 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004209691,0.00130759,0.0006799009,0.005537969,0.004460403,0.005295961,0.002230128,0.0005898786,0.3636523],"category_scores_gemma":[0.002831516,0.0007373731,0.0005781893,0.02145776,0.0006088591,0.001685758,0.001638669,0.0008668148,0.1756915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01764433,"about_ca_system_score_gemma":0.05111157,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9569476,"about_ca_topic_score_gemma":0.9708571,"domain_scores_codex":[0.9988548,0.00003482937,0.00003299541,0.0001310564,0.0007433508,0.0002029789],"domain_scores_gemma":[0.9978117,0.00005321519,0.00005131128,0.0001418114,0.001717461,0.000224508],"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":[0.000032886,0.00001100454,0.0008709856,0.0001136035,0.0000040326,0.00003337726,0.0002121801,0.0002634909,0.0001131744,0.003459011,0.9611914,0.03369496],"study_design_scores_gemma":[0.00000651721,0.00000294846,0.003443815,0.00003967994,0.000003490098,0.00002426495,0.0001957769,0.0001956213,0.0002156874,0.000333194,0.9955246,0.00001423992],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002221866,0.000451774,0.002770189,0.0003714325,0.0001621481,0.0002501068,0.515029,0.004057227,0.4746864],"genre_scores_gemma":[0.01693154,0.001215648,0.01036695,0.0001510563,0.0000688241,0.0002826102,0.3764614,0.003069471,0.5914525],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3636523,"threshold_uncertainty_score":0.9076728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500113749670364,"score_gpt":0.2070048679352403,"score_spread":0.1920037304385366,"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."}}