{"id":"W4389680290","doi":"10.5194/isprs-annals-x-1-w1-2023-1151-2023","title":"Preface: ISPRS Geospatial Week 2023","year":2023,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Arab Academy for Science, Technology and Maritime Transport","keywords":"Geospatial analysis; Geomatics; Photogrammetry; Geography; Analytics; Remote sensing; Cartography; Library science; Computer science; Data science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005962292,0.001837016,0.001125571,0.007049505,0.002488715,0.009464702,0.002334747,0.003334834,0.3510435],"category_scores_gemma":[0.009575345,0.000745122,0.001293883,0.005725975,0.0008010795,0.004735302,0.002933313,0.004313414,0.3194742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002111127,"about_ca_system_score_gemma":0.004320635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01083656,"about_ca_topic_score_gemma":0.01032399,"domain_scores_codex":[0.9970424,0.0003973855,0.0002555914,0.0002813506,0.00177646,0.0002468647],"domain_scores_gemma":[0.9829463,0.001267903,0.0006757713,0.001932023,0.0113939,0.001784194],"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":[0.00002147632,0.00001063855,0.00005134994,0.00005676693,0.000001637405,0.00002123237,0.000008449939,0.0000475298,0.0001091149,0.0002363294,0.9922251,0.007210433],"study_design_scores_gemma":[0.000006913471,0.00000871984,0.000460114,0.00007770382,9.981002e-7,0.00001830425,0.00002109516,0.00007852708,0.0001125561,0.0003510604,0.9988557,0.00000832916],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00178382,0.004552525,0.0151014,0.03028577,0.1870585,0.003342132,0.1677441,0.009126273,0.5810055],"genre_scores_gemma":[0.008832689,0.003487353,0.007261125,0.008007881,0.03571183,0.002159911,0.144654,0.007621083,0.7822641],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6489565,"threshold_uncertainty_score":0.9256577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04362837179112076,"score_gpt":0.2969089690003328,"score_spread":0.253280597209212,"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."}}