{"id":"W3100362654","doi":"10.5194/isprs-archives-xliv-3-w1-2020-1-2020","title":"GEOINFORMATION FOR DISASTER MANAGEMENT 2020 (Gi4DM2020): PREFACE","year":2020,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Knowledge Management and Technology","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emergency management; Geographic information system; Geography; Computer science; Data science; Environmental planning; Political science; Cartography","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":[0.002650908,0.001577461,0.0006282889,0.002269593,0.0006778073,0.004218231,0.001343151,0.002854613,0.151626],"category_scores_gemma":[0.003947348,0.0003587725,0.0004376445,0.001989085,0.0005233163,0.003900866,0.0030597,0.003019504,0.1315279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001387996,"about_ca_system_score_gemma":0.003026417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006418762,"about_ca_topic_score_gemma":0.003608261,"domain_scores_codex":[0.9996048,0.0000658464,0.00003028476,0.00005341091,0.0001766898,0.00006904112],"domain_scores_gemma":[0.9973143,0.0002700659,0.0001675381,0.0001332877,0.001400593,0.0007142067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002681729,0.00001151244,0.00007682135,0.0002730987,0.000002119706,0.00001976429,0.00001365713,0.0002819446,0.0002052016,0.001871199,0.9651634,0.03205436],"study_design_scores_gemma":[0.000006608713,0.00001522114,0.0002445492,0.0002056587,0.000001751617,0.00001205012,0.00001350458,0.0001404155,0.00005755754,0.001040904,0.9982569,0.000004966289],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"editorial","genre_scores_codex":[0.001915151,0.03534359,0.01589675,0.0799377,0.2155861,0.001936858,0.1306666,0.007315527,0.5114017],"genre_scores_gemma":[0.02071943,0.0749599,0.01712399,0.0275969,0.06285251,0.003021722,0.262518,0.00507812,0.5261294],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.151626,"threshold_uncertainty_score":0.5072395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03671486436748621,"score_gpt":0.2949591138640807,"score_spread":0.2582442494965945,"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."}}