{"id":"W2562128244","doi":"10.15551/scigeo.v61i1.353","title":"SPATIAL DATA INFRASTRUCTURE. BENEFITS AND STRATEGY","year":2015,"lang":"ro","type":"article","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Spatial data infrastructure; Context (archaeology); Data sharing; Spatial analysis; Information infrastructure; Scale (ratio); Data access; Order (exchange); Data science; Computer science; Business; Information system; Geography; Political science; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.00126331,0.0001836998,0.0002591027,0.0001020252,0.0004918447,0.0003332437,0.0005778077,0.000166682,0.0002259857],"category_scores_gemma":[0.0002412181,0.0001547424,0.00002255747,0.0003743529,0.0004432756,0.001071249,0.0007369309,0.0001328038,0.0001587732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003370297,"about_ca_system_score_gemma":0.0002788163,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02408303,"about_ca_topic_score_gemma":0.02295224,"domain_scores_codex":[0.99808,0.00009490673,0.0004269163,0.0003087457,0.0007052485,0.0003841601],"domain_scores_gemma":[0.9986101,0.00007099863,0.0001979767,0.0004862824,0.0003398876,0.0002947141],"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":[0.00003879187,0.00004859663,0.3152232,0.000103831,0.0002982229,0.00000474946,0.1055205,0.0002421294,0.000001291564,0.180552,0.143233,0.2547337],"study_design_scores_gemma":[0.001762483,0.0002779137,0.2640906,0.00009394451,0.0001143136,0.0000168561,0.3204371,0.00363475,0.000005291718,0.005840309,0.4028533,0.0008730694],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2420902,0.007011701,0.0005857515,0.004100661,0.004210603,0.001100287,0.000484249,0.0002286808,0.7401879],"genre_scores_gemma":[0.9971714,0.0005893379,0.000194895,0.0001728852,0.0005022983,0.000003414338,0.00004072558,0.000006581538,0.001318449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7550812,"threshold_uncertainty_score":0.9948763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1059163641518977,"score_gpt":0.3178187501684184,"score_spread":0.2119023860165207,"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."}}