{"id":"W2619183179","doi":"10.1016/j.geomorph.2017.05.016","title":"Semi-automatic mapping of linear-trending bedforms using ‘Self-Organizing Maps’ algorithm","year":2017,"lang":"en","type":"article","venue":"Geomorphology","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Mars Exploration Program; Computer science; Remote sensing; Automation; Artificial intelligence; Self-organizing map; Photogrammetry; Artificial neural network; Satellite; Algorithm; Satellite imagery; Earth observation; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004431502,0.0005165396,0.0005616294,0.001889287,0.0003783923,0.0006404434,0.0007864198,0.0004029138,0.001213261],"category_scores_gemma":[0.0007768651,0.0003557017,0.0007227734,0.001247455,0.0002523438,0.0004585274,0.0005087783,0.0002739637,0.0005332527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001575213,"about_ca_system_score_gemma":0.0007585012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005374125,"about_ca_topic_score_gemma":0.008838583,"domain_scores_codex":[0.9996536,0.00006410448,0.00002598963,0.0001024658,0.0001052237,0.00004861984],"domain_scores_gemma":[0.9995165,0.0001516934,0.00003924366,0.00006202812,0.0002073738,0.0000232591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004274955,0.0002513368,0.006868372,0.0002528128,0.00016584,0.0002136168,0.0002485691,0.08218271,0.05934355,0.001667355,0.006437202,0.8419412],"study_design_scores_gemma":[0.000015156,0.00004626502,0.008800201,0.00001071887,0.00003406924,0.0001002683,0.00006586336,0.9755108,0.01261308,0.001055662,0.001722343,0.0000256123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1408558,0.0001547156,0.8536202,0.0000604299,0.00006316352,0.0001200841,0.000593,0.003200768,0.001331837],"genre_scores_gemma":[0.5741264,0.0000907221,0.4216357,0.00003777322,0.00002945307,0.0001203887,0.001712993,0.0001441804,0.002102369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005374125,"threshold_uncertainty_score":0.01068568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02231849789998868,"score_gpt":0.2624384221693539,"score_spread":0.2401199242693652,"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."}}