{"id":"W4225003957","doi":"10.1029/2021je006879","title":"Analysis of Venusian Wrinkle Ridge Morphometry Using Stereo‐Derived Topography: A Case Study From Southern Eistla Regio","year":2022,"lang":"en","type":"article","venue":"Journal of Geophysical Research Planets","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education and Science of the Russian Federation","keywords":"Wrinkle; Geology; Lithosphere; Ridge; Geometry; Venus; Mantle (geology); Deformation (meteorology); Seismology; Paleontology; Tectonics; Materials science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003086495,0.0002120747,0.0001771269,0.001051245,0.0002325923,0.0004235921,0.0002699577,0.0002028649,0.0003251285],"category_scores_gemma":[0.0005098011,0.0001141943,0.0004627248,0.001110078,0.0002675004,0.0001241838,0.0002352993,0.00008508906,0.0001121427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003950214,"about_ca_system_score_gemma":0.0002776466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06386129,"about_ca_topic_score_gemma":0.1362524,"domain_scores_codex":[0.9998738,0.00002511917,0.000007879831,0.00003015905,0.00003016434,0.00003286697],"domain_scores_gemma":[0.9997345,0.00005350641,0.00006015422,0.0000617689,0.00006654917,0.00002361668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001275435,0.00007376027,0.9527029,0.00006170393,0.0001630754,0.002980607,0.001298181,0.009676724,0.01479239,0.0001172636,0.0002059788,0.01779977],"study_design_scores_gemma":[0.000004885437,0.00003841269,0.990692,0.00000657731,0.00003003037,0.0003362849,0.001026136,0.006199872,0.001141615,0.00002866868,0.0004877495,0.000007748376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994649,0.00002029858,0.0001525409,0.000003518649,4.851373e-7,0.000004044216,0.0001385974,0.000008595051,0.0002068971],"genre_scores_gemma":[0.9991818,0.00002318173,0.0003695899,0.000002019151,0.000001043709,0.000002017092,0.0003115074,0.000002909774,0.0001059329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06386129,"threshold_uncertainty_score":0.1269791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09523712043013836,"score_gpt":0.354778205318681,"score_spread":0.2595410848885426,"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."}}