{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005443231,0.000514825,0.0001967566,0.002397139,0.001607288,0.00878931,0.001375604,0.002402413,0.01413346],"category_scores_gemma":[0.008726964,0.0003312167,0.0003243697,0.004125267,0.002108815,0.006264145,0.004541459,0.001397101,0.005692254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007587382,"about_ca_system_score_gemma":0.01942649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02435811,"about_ca_topic_score_gemma":0.01795589,"domain_scores_codex":[0.9959122,0.001537046,0.0002316126,0.0002926225,0.001677154,0.0003493409],"domain_scores_gemma":[0.9939607,0.001061625,0.0003788222,0.0004806436,0.003174003,0.0009442035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003607548,0.0001154678,0.004181235,0.000493649,0.00001604239,0.0002520273,0.0009350956,0.001437042,0.0005406796,0.7607304,0.06653569,0.1647266],"study_design_scores_gemma":[0.00001814124,0.0000738909,0.003275767,0.0003662432,0.0000140098,0.0003081514,0.003084794,0.001249244,0.000514118,0.04634235,0.944735,0.00001819038],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01407102,0.003977093,0.02851449,0.152718,0.0007056046,0.00112144,0.002195967,0.000864165,0.7958322],"genre_scores_gemma":[0.5898637,0.01423618,0.1216562,0.02102056,0.0009295265,0.001514657,0.005403359,0.0004218654,0.2449539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02435811,"threshold_uncertainty_score":0.05505061,"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."}}