{"id":"W2066219533","doi":"10.1177/0018720811399757","title":"Viewpoint Tethering for Remotely Operated Vehicles: Effects on Complex Terrain Navigation and Spatial Awareness","year":2011,"lang":"en","type":"article","venue":"Human Factors The Journal of the Human Factors and Ergonomics Society","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Research and Development Canada","keywords":"Endocentric and exocentric; Terrain; Task (project management); Computer science; Computer vision; Human–computer interaction; Heading (navigation); Artificial intelligence; Simulation; Engineering","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":[0.0001925246,0.0003741429,0.0001580156,0.0001323638,0.0001055853,0.0002888385,0.0002030171,0.0002297684,0.002848723],"category_scores_gemma":[0.002546998,0.0001544031,0.0002229066,0.00006952297,0.0001973127,0.0002961846,0.0004851898,0.0001885111,0.0001731745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009629101,"about_ca_system_score_gemma":0.0001604818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006717501,"about_ca_topic_score_gemma":0.00101031,"domain_scores_codex":[0.9998529,0.0000516263,0.000008879192,0.00002888231,0.00003688777,0.00002086721],"domain_scores_gemma":[0.9987525,0.0007572756,0.0001912679,0.0001019306,0.00009579686,0.0001012071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.004235805,0.0005499686,0.01483198,0.000551114,0.00007415716,0.0006509312,0.002217432,0.001835381,0.9078539,0.0002284467,0.000266105,0.06670486],"study_design_scores_gemma":[0.000856129,0.03940602,0.6444717,0.0002249568,0.0006571284,0.003444443,0.004031739,0.0111905,0.2880046,0.0007646297,0.006785074,0.0001630264],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982931,0.00009351748,0.001095434,0.00001283812,0.000005673427,0.00001364326,0.00001798133,0.00002291259,0.0004448209],"genre_scores_gemma":[0.9967383,0.0001083541,0.002714545,0.00001552869,0.000005080933,0.00002234845,0.00003424746,0.00001364692,0.0003478575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002848723,"threshold_uncertainty_score":0.009529889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08552461068149239,"score_gpt":0.3389086011033306,"score_spread":0.2533839904218382,"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."}}