{"id":"W6968061029","doi":"10.5281/zenodo.2555353","title":"Federated Geospatial Data Discovery for Canada - Geodisy","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Geospatial analysis; Summit; Interface (matter); Data discovery; Data integration; Web Coverage Service; Presentation (obstetrics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007225506,0.001149619,0.0008090039,0.003025285,0.005283564,0.009330962,0.003187726,0.00193215,0.0421215],"category_scores_gemma":[0.0103928,0.0007214394,0.0007576633,0.004802188,0.00167551,0.006384215,0.007589388,0.002555782,0.01244235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0251266,"about_ca_system_score_gemma":0.06497046,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8802565,"about_ca_topic_score_gemma":0.9176884,"domain_scores_codex":[0.9962998,0.0002396252,0.00009973434,0.0003056729,0.002402734,0.0006525078],"domain_scores_gemma":[0.9900703,0.0007889391,0.000112937,0.000723544,0.006430086,0.001874244],"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":[0.0001460059,0.00002578605,0.000633166,0.0000576261,0.00002074261,0.00008561659,0.0002264938,0.001313292,0.0009379946,0.0151075,0.9493576,0.03208816],"study_design_scores_gemma":[0.00007522517,0.00001589113,0.0009152503,0.00008500474,0.00001831275,0.00004379213,0.0003698201,0.01470314,0.001903279,0.007844694,0.973959,0.00006666355],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02213821,0.006303925,0.2778469,0.1455475,0.01178485,0.001737425,0.1489664,0.1410725,0.2446024],"genre_scores_gemma":[0.1325276,0.007079856,0.2263431,0.01866987,0.001739907,0.0008395006,0.2378055,0.01603676,0.3589579],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1197435,"threshold_uncertainty_score":0.2408973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06083133172259895,"score_gpt":0.2989026124582812,"score_spread":0.2380712807356823,"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."}}