{"id":"W4285154332","doi":"10.1007/978-3-030-53125-6_18","title":"Registration of Geospatial Information Elements","year":2022,"lang":"en","type":"book-chapter","venue":"Springer handbooks","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Infineon Technologies (Canada)","funders":"","keywords":"Geospatial analysis; Metadata; Geospatial metadata; Cadastre; Computer science; Standardization; Information retrieval; Feature (linguistics); Interoperability; Volunteered geographic information; Geographic information system; Geography; Data element; Database; Data science; World Wide Web; Meta Data Services; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000953644,0.0006700145,0.0008824361,0.003269293,0.0007982304,0.004808066,0.001729132,0.001055756,0.02333109],"category_scores_gemma":[0.002953871,0.0006564501,0.0008273957,0.007599778,0.0008622642,0.004122464,0.00240517,0.001410094,0.02129452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007789095,"about_ca_system_score_gemma":0.001450296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00285831,"about_ca_topic_score_gemma":0.003046113,"domain_scores_codex":[0.9990128,0.0001308934,0.00009952222,0.0001997453,0.0005063626,0.00005053344],"domain_scores_gemma":[0.9991634,0.0001627055,0.00005057909,0.0004505833,0.0001437935,0.00002897223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000890698,0.00007536049,0.0008340963,0.0005190342,0.0000405702,0.0002632804,0.0006953252,0.004355217,0.01779304,0.2423479,0.05152692,0.6814601],"study_design_scores_gemma":[0.00001381313,0.00003812427,0.0009934267,0.0002074397,0.00004069819,0.0006917863,0.0004064318,0.01409862,0.02743451,0.07485134,0.8811752,0.00004861273],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.006731296,0.002462215,0.8537253,0.0006263246,0.001051848,0.0002508637,0.00291479,0.01036696,0.1218705],"genre_scores_gemma":[0.07015969,0.006447863,0.7265067,0.0004372162,0.0002914094,0.0002550517,0.0196194,0.004382747,0.1719001],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02333109,"threshold_uncertainty_score":0.0780502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01899575714836,"score_gpt":0.2212782596070448,"score_spread":0.2022825024586848,"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."}}