{"id":"W156033958","doi":"10.22260/isarc2013/0033","title":"Self-Localization System for Robots Using Random Dot Floor Patterns","year":2013,"lang":"en","type":"article","venue":"Proceedings of the ... ISARC","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Robot; Position (finance); Artificial intelligence; Computer science; Construct (python library); Matching (statistics); Computer vision; Space (punctuation); Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003716096,0.0003813155,0.0004729879,0.0006502065,0.0002831365,0.0004237541,0.0007610346,0.0004418312,0.002203903],"category_scores_gemma":[0.0009555679,0.0002034708,0.0002672605,0.0006074729,0.0002992489,0.0006870819,0.000776875,0.0002367779,0.0007169771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003541015,"about_ca_system_score_gemma":0.0003547239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001105973,"about_ca_topic_score_gemma":0.0007295544,"domain_scores_codex":[0.9996148,0.00005817803,0.00002526614,0.00009112851,0.0001721611,0.00003834486],"domain_scores_gemma":[0.9993513,0.0001136193,0.0001020457,0.0001395903,0.0002392073,0.00005417907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007372794,0.0003141664,0.005673259,0.0002170733,0.00009525543,0.0004279039,0.0006047714,0.05995536,0.4271638,0.006993545,0.003766906,0.4940506],"study_design_scores_gemma":[0.0001001579,0.0007622411,0.005792407,0.00002478837,0.00005368294,0.0005749103,0.0001563375,0.7915581,0.1889533,0.001915108,0.01004127,0.00006777524],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1417334,0.0001262354,0.8522398,0.00008166028,0.00005924876,0.0000966677,0.00005333348,0.003371046,0.002238564],"genre_scores_gemma":[0.7579194,0.00007206903,0.2381479,0.00005929232,0.00001230339,0.0001081825,0.000125769,0.0000773522,0.003477801],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002203903,"threshold_uncertainty_score":0.007372797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060681353391142,"score_gpt":0.1956180971809506,"score_spread":0.1850112836470391,"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."}}