{"id":"W6926570724","doi":"10.21227/fwqe-mc97","title":"The Canadian Planetary Emulation Terrain Energy-Aware Rover Navigation Dataset","year":2021,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Terrain; Digital elevation model; Emulation; Visualization; Georeference; Data visualization; Mars Exploration Program; Elevation (ballistics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0006036073,0.002041781,0.001118841,0.003314539,0.002662641,0.001928466,0.003798199,0.001345437,0.01826121],"category_scores_gemma":[0.00300711,0.0004702971,0.0009232272,0.008438934,0.0006847336,0.0009238406,0.001816768,0.001781355,0.02056486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008403773,"about_ca_system_score_gemma":0.01527209,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8913506,"about_ca_topic_score_gemma":0.9587853,"domain_scores_codex":[0.9991086,0.00005735865,0.0000419813,0.0001862128,0.0003831066,0.0002226993],"domain_scores_gemma":[0.997806,0.0001423647,0.00006709987,0.000288807,0.001455365,0.0002403645],"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":[0.00003883689,0.00001961951,0.001533139,0.0001976344,0.00003085266,0.00003371811,0.00004376179,0.0008592081,0.0001579336,0.0006316382,0.9931622,0.003291436],"study_design_scores_gemma":[0.00007764658,0.000008671388,0.01167634,0.0002054021,0.00003165314,0.00005454972,0.0002262298,0.001798449,0.0006997656,0.0008412926,0.9843131,0.00006686147],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000498568,0.00007679241,0.0001377427,0.00007657186,0.00002158622,0.00001686487,0.9972141,0.000415107,0.001542601],"genre_scores_gemma":[0.0009208121,0.00005362717,0.0004521639,0.0000295349,0.000003261158,0.00003046395,0.9977161,0.0000681658,0.0007258925],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1086494,"threshold_uncertainty_score":0.2185785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01702591047623424,"score_gpt":0.2647693120640487,"score_spread":0.2477434015878144,"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."}}