{"id":"W182188404","doi":"10.1007/978-3-642-21538-4_4","title":"Toward Opportunistic Collaboration in Target Pursuit Problems","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Observability; Computer science; Robot; Inference; Action (physics); Relation (database); Artificial intelligence; Inference engine; Distributed computing; Data mining; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001564686,0.0006133504,0.0006782558,0.001287537,0.0001533025,0.0006718491,0.004454139,0.0004433858,0.0000293311],"category_scores_gemma":[0.0001839549,0.000598527,0.00008049649,0.00121975,0.0005324472,0.0008839752,0.001198067,0.0009525676,0.00008987632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005136359,"about_ca_system_score_gemma":0.001504263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005665683,"about_ca_topic_score_gemma":0.00004320562,"domain_scores_codex":[0.9951682,0.00006389367,0.0007880572,0.001840572,0.001258612,0.0008806367],"domain_scores_gemma":[0.9972841,0.000286201,0.0004302414,0.001430477,0.0003164339,0.0002525142],"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":[0.00001417171,0.0001756794,0.0005729205,0.0002336578,0.00002878991,0.001870247,0.01139697,0.3043278,0.0002025048,0.09175504,0.0002037626,0.5892184],"study_design_scores_gemma":[0.0003070702,0.0002400181,0.0002125751,0.0006134656,0.000005728106,0.0001038549,3.246456e-7,0.7234214,0.0001756713,0.2726195,0.001475272,0.0008251451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000009043399,0.0003345577,0.9890953,0.0009112396,0.002629327,0.0006621671,0.00001106591,0.0002055562,0.006141767],"genre_scores_gemma":[0.02714696,0.00004444657,0.9707449,0.0009257255,0.0003291683,0.00003351375,0.00002350677,0.0000503002,0.0007014688],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5883933,"threshold_uncertainty_score":0.9996466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0459958402866514,"score_gpt":0.2621389272186543,"score_spread":0.2161430869320029,"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."}}