{"id":"W2553980427","doi":"","title":"INCREASING INTEROPERABILITY WITH CEONET TECHNOLOGY USING WSDL AND SOAP","year":2002,"lang":"en","type":"article","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"WS-I Basic Profile; SOAP; Web service; World Wide Web; Devices Profile for Web Services; Computer science; Interoperability; WS-Policy; WS-Addressing; Web standards; Web Coverage Service; Web modeling; Service-oriented architecture; Web development; Web application security; Web mapping","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":[0.00334497,0.0004681491,0.0002640391,0.001651732,0.0008160691,0.002850427,0.0008287493,0.0007179012,0.001722618],"category_scores_gemma":[0.006726569,0.0003364825,0.0004480328,0.001678514,0.0009118102,0.004836203,0.001877207,0.001218444,0.001154291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002121635,"about_ca_system_score_gemma":0.004733718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009786749,"about_ca_topic_score_gemma":0.01307521,"domain_scores_codex":[0.996732,0.000643651,0.0002933752,0.0001992814,0.001920045,0.0002117613],"domain_scores_gemma":[0.9976571,0.0004534058,0.0001444757,0.000384246,0.001223075,0.0001376864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001649282,0.0003893337,0.004433677,0.0004667974,0.00005533418,0.0009787069,0.003068353,0.01918587,0.04174898,0.4832312,0.02626557,0.4200111],"study_design_scores_gemma":[0.00007789201,0.0001329381,0.001540553,0.0002202463,0.00006310691,0.0006008845,0.0007253973,0.08806252,0.04841839,0.08375167,0.7762846,0.0001217452],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03080693,0.0005503953,0.8735778,0.002961163,0.000457979,0.0004094605,0.0002568231,0.004759855,0.0862196],"genre_scores_gemma":[0.1906553,0.001722031,0.7670475,0.000847935,0.0001533813,0.0005108207,0.001548186,0.0005556308,0.03695929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009786749,"threshold_uncertainty_score":0.01945961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03861578373642022,"score_gpt":0.2705803133824403,"score_spread":0.2319645296460201,"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."}}