{"id":"W6931884870","doi":"10.5683/sp3/7pwn0w","title":"MVSMMP Map 04 Landslide Susceptibility","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Landslide; Hazard; Hazard map; Yield (engineering); Landslide classification","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003618206,0.0002677384,0.0003072292,0.0001899273,0.00006851546,0.0006383442,0.001838165,0.0002099191,0.0001587404],"category_scores_gemma":[0.00009766666,0.0002295076,0.0001347081,0.00035603,0.00005139822,0.000222834,0.0007702365,0.0002948234,0.002128806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006324151,"about_ca_system_score_gemma":0.0001885169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004685188,"about_ca_topic_score_gemma":0.0105673,"domain_scores_codex":[0.9981577,0.00007397596,0.0003490156,0.0006827808,0.000450282,0.0002861925],"domain_scores_gemma":[0.9976239,0.00005604012,0.0001116865,0.001963432,0.00008857448,0.0001563372],"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":[8.848663e-7,0.00004128254,0.000005930453,0.000177146,0.00002815416,0.00006699692,0.00002082318,0.000001595736,3.185322e-7,0.002578371,0.9964585,0.0006199931],"study_design_scores_gemma":[0.00007788966,0.00002636618,0.00001802969,0.0000707049,0.00004265065,0.000006295153,0.000006051538,0.001129242,0.00000608457,0.001275501,0.9970708,0.0002703382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[9.052987e-8,0.0001461674,0.009683628,0.0007852975,0.0006018433,0.0001040726,0.987877,0.000223024,0.0005788672],"genre_scores_gemma":[0.000001309823,0.0001900457,0.0008553234,0.001069384,0.0003207485,0.000008118377,0.9969409,0.00001353398,0.0006006919],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009063835,"threshold_uncertainty_score":0.9986482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02236990228142176,"score_gpt":0.3074548530563111,"score_spread":0.2850849507748893,"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."}}