{"id":"W1970669897","doi":"10.1016/j.ipl.2011.07.018","title":"How many oblivious robots can explore a line","year":2011,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais; University of Ottawa","funders":"Agence Nationale de la Recherche","keywords":"Asynchronous communication; Robot; Impossibility; Computer science; Line (geometry); Theoretical computer science; Mobile robot; Node (physics); Combinatorics; Distributed computing; Artificial intelligence; Mathematics; Computer network; Physics","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":[0.0009012806,0.0004624951,0.0006204838,0.0003386704,0.001063874,0.001913599,0.00116329,0.001418891,0.00669868],"category_scores_gemma":[0.007256211,0.0004216521,0.0004691824,0.0005636208,0.001558907,0.005637109,0.001659383,0.001425627,0.000852598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006964583,"about_ca_system_score_gemma":0.0007925191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008196172,"about_ca_topic_score_gemma":0.001175147,"domain_scores_codex":[0.9993318,0.000241393,0.00003622246,0.0001561825,0.00009047239,0.0001440143],"domain_scores_gemma":[0.9969872,0.001907985,0.000238934,0.000528541,0.0001481083,0.0001893772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001707315,0.0002574175,0.004498696,0.0005630443,0.0002567122,0.0001779863,0.0007747339,0.4909207,0.007052832,0.2895738,0.01532241,0.1888942],"study_design_scores_gemma":[0.0001271241,0.0002587185,0.0008227075,0.0000636059,0.0000911255,0.0001657827,0.000536617,0.557677,0.004709796,0.4275558,0.007959676,0.00003208393],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5203198,0.002107785,0.4147348,0.009901595,0.000261269,0.0001497844,0.000357492,0.001351748,0.05081567],"genre_scores_gemma":[0.9354521,0.0005413452,0.05211351,0.0002807441,0.00006851187,0.0001078056,0.000164944,0.000193783,0.01107721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00669868,"threshold_uncertainty_score":0.02240926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05675376930657339,"score_gpt":0.2349867679873912,"score_spread":0.1782329986808179,"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."}}