{"id":"W2802148751","doi":"10.4095/288846","title":"The Canadian Geospatial Data Infrastructure, achieving the vision of the CGDI","year":2005,"lang":"en","type":"report","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Data science; Computer science; Spatial data infrastructure; Geography; Business; Cartography; Remote sensing; 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":[0.006038377,0.0001892702,0.0002600017,0.00009181083,0.006231295,0.0003280499,0.003081322,0.0002863443,0.0001745536],"category_scores_gemma":[0.001734561,0.00007541294,0.0001403724,0.0005193882,0.0009810631,0.0002440387,0.0008058701,0.0005070663,0.00001479029],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003558878,"about_ca_system_score_gemma":0.005723852,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9152607,"about_ca_topic_score_gemma":0.9963109,"domain_scores_codex":[0.9962087,0.0002837774,0.0006817183,0.0002046732,0.002167719,0.0004533694],"domain_scores_gemma":[0.9963768,0.0003976563,0.0008017504,0.001539808,0.0007994344,0.00008460537],"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":[0.000004141883,0.000007447192,0.05316333,0.00008178776,0.0004566229,8.314539e-7,0.03244115,0.0000633467,3.211468e-7,0.02453577,0.7455719,0.1436733],"study_design_scores_gemma":[0.00002762426,0.000003469734,0.135752,0.00005420626,0.0000268422,0.000002469533,0.006900219,0.00001567945,1.364048e-7,0.0001172018,0.8570123,0.00008783845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0005497227,0.00106534,0.00001342447,0.01033027,0.004222926,0.001018468,0.0001955866,0.00002986756,0.9825744],"genre_scores_gemma":[0.9753508,0.003018498,0.00004862495,0.0003492126,0.001947621,0.00002425724,0.00005949591,0.00001763016,0.01918384],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9748011,"threshold_uncertainty_score":0.9999128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05122717494216866,"score_gpt":0.3585049624342861,"score_spread":0.3072777874921175,"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."}}