{"id":"W6987628004","doi":"","title":"Toward a 3d marine cadastre in support of good ocean governance","year":2001,"lang":"en","type":"article","venue":"Research Repository (Delft University of Technology)","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Cadastre; Marine spatial planning; Corporate governance; Quality (philosophy); Key (lock); Data quality; Marine biodiversity","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002075268,0.00009511992,0.0002085112,0.0004127374,0.00006904332,0.00000380371,0.0006165041,0.0002102293,0.0000301949],"category_scores_gemma":[0.00003218921,0.0001236648,0.00004529982,0.0009464817,0.0003206785,0.00009110981,0.0002988056,0.0004829995,0.00000929086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002291109,"about_ca_system_score_gemma":0.00009126574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000961056,"about_ca_topic_score_gemma":0.0001753597,"domain_scores_codex":[0.998934,0.0000222289,0.0002014881,0.0002148661,0.0003158419,0.0003116227],"domain_scores_gemma":[0.9991574,0.00003576609,0.00005634596,0.0004849606,0.0002110338,0.00005448435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004377373,0.001791353,0.5240831,0.001585863,0.0005516619,0.002851876,0.002006383,0.1400211,0.2095675,0.03780336,0.01864682,0.06065324],"study_design_scores_gemma":[0.006999495,0.002058617,0.2053182,0.0008746748,0.000157856,0.0006729648,0.005922113,0.3011329,0.2424541,0.008545601,0.2237532,0.002110241],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979279,0.00009393629,0.002088437,0.0004802487,0.00003295559,0.0002231217,0.00001404468,0.0002105857,0.0175777],"genre_scores_gemma":[0.991981,0.0003682899,0.006566889,0.000001090803,0.00001139877,9.980143e-7,0.000004282892,0.00001383684,0.001052182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3187649,"threshold_uncertainty_score":0.5042904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01923492462180596,"score_gpt":0.2378078435432991,"score_spread":0.2185729189214931,"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."}}