{"id":"W2980139086","doi":"","title":"Canadian Geospatial Data Infrastructure (CGDI) Access Services","year":2001,"lang":"en","type":"article","venue":"The 81st AMS Annual Meeting","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Business; Data access; Computer science; Spatial data infrastructure; Data science; Database; Remote sensing; Geography; Spatial analysis","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0016339,0.0001357062,0.0001567625,0.0001124354,0.002451447,0.0004244767,0.001997318,0.00009483825,0.0002153883],"category_scores_gemma":[0.0001895063,0.00009870084,0.0000333868,0.0006401947,0.0001743098,0.001385685,0.0005287992,0.0001778007,0.0001192571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008863457,"about_ca_system_score_gemma":0.0002121682,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8530539,"about_ca_topic_score_gemma":0.9252365,"domain_scores_codex":[0.9982879,0.0001495108,0.0003002963,0.0002018432,0.0004875642,0.0005729517],"domain_scores_gemma":[0.9987394,0.0001186467,0.0001962437,0.0005056328,0.0002746265,0.0001654355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001910933,0.00001106893,0.5818064,0.00006590841,0.0001475793,0.00001171514,0.3635706,0.0007212629,0.000003708705,0.005118339,0.0219002,0.0266241],"study_design_scores_gemma":[0.0001441987,0.000009169883,0.06443141,0.00007731793,0.00002239263,0.000005657007,0.16238,0.0004143432,0.000001588717,0.0006688841,0.7716163,0.0002287641],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6811788,0.0002825779,0.00002517675,0.01039278,0.001316866,0.0005546247,0.0002525329,0.0001630295,0.3058336],"genre_scores_gemma":[0.9971594,0.0001032839,0.00005081368,0.0009468057,0.0008980155,0.00001112103,0.00004964364,0.000009795098,0.000771174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.749716,"threshold_uncertainty_score":0.9988472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02631990063678509,"score_gpt":0.3145847875344069,"score_spread":0.2882648868976218,"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."}}