{"id":"W4205525589","doi":"10.3390/geomatics2010003","title":"Evaluating Scaling Frameworks for Multiscale Geomorphometric Analysis","year":2022,"lang":"en","type":"article","venue":"Geomatics","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Division of Earth Sciences; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Scaling; Computer science; Convolution (computer science); Resampling; Gaussian; Sizing; Interpolation (computer graphics); Scale (ratio); Algorithm; Quadratic equation; Mathematical optimization; Mathematics; Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008057829,0.00009237747,0.0001810063,0.0001300912,0.0005634071,0.00003387564,0.0002177299,0.00008766609,0.005491717],"category_scores_gemma":[0.0001518262,0.00007952166,0.000168026,0.001799295,0.00003500827,0.00004483885,0.0003124775,0.0002900737,0.00005618615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001512465,"about_ca_system_score_gemma":0.000006886667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009527749,"about_ca_topic_score_gemma":0.00001115007,"domain_scores_codex":[0.9987334,0.00005065916,0.0002551305,0.000217042,0.0004692481,0.0002745361],"domain_scores_gemma":[0.9993423,0.0002257061,0.0001213551,0.0002348547,0.000009089228,0.00006668971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001111416,0.00007478196,0.03176714,0.000008996172,0.00017204,0.000002716765,0.000539785,0.9337195,0.0001963973,0.00002522265,0.001184865,0.03229748],"study_design_scores_gemma":[0.000353343,0.00008596751,0.01481609,0.000002846124,0.0004707133,0.000004445391,0.0003136663,0.9795696,0.00005573652,0.001004069,0.00316669,0.00015681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9251943,0.00008972177,0.07318505,0.0001434485,0.0002076807,0.0002939739,0.00004335094,0.00004674327,0.0007957015],"genre_scores_gemma":[0.9400001,0.000006146375,0.05881611,0.0002042733,0.00003059263,0.00008264094,0.00005534684,0.0000144112,0.0007903557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04585016,"threshold_uncertainty_score":0.9954174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0248483422473639,"score_gpt":0.3046671004596846,"score_spread":0.2798187582123207,"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."}}