{"id":"W4399261823","doi":"10.1609/socs.v17i1.31557","title":"Bi-Criteria Diverse Plan Selection via Beam Search Approximation","year":2024,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Selection (genetic algorithm); Plan (archaeology); Computer science; Information retrieval; Mathematical optimization; Mathematics; Artificial intelligence; Biology","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":[0.003100307,0.001544351,0.001672145,0.001308836,0.000614455,0.001496356,0.001844624,0.001621226,0.004618786],"category_scores_gemma":[0.0074376,0.0008038204,0.001318702,0.001953995,0.00121319,0.001460683,0.001805194,0.001935923,0.0008116242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001610479,"about_ca_system_score_gemma":0.002088466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004487032,"about_ca_topic_score_gemma":0.00474223,"domain_scores_codex":[0.9980136,0.0008161095,0.00007117518,0.0002397203,0.000595185,0.0002641119],"domain_scores_gemma":[0.9969381,0.002192646,0.0001932007,0.0002486902,0.0002894952,0.0001377955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001198824,0.00007792509,0.0006099765,0.00009601582,0.00005194407,0.00007213253,0.00006477226,0.9344933,0.0008638784,0.02238966,0.002865436,0.03829511],"study_design_scores_gemma":[0.00002610842,0.00003631854,0.00005641506,0.00001555049,0.000008956566,0.00002277176,0.0000155198,0.9906688,0.0002456141,0.008290642,0.0006089536,0.000004452143],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01151964,0.0004136451,0.9834064,0.0002581026,0.00002339236,0.000111385,0.0001153453,0.0004697053,0.003682339],"genre_scores_gemma":[0.3202175,0.0004651773,0.6747497,0.0003710135,0.00004069065,0.0006004545,0.0004274704,0.0002380753,0.002890014],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004618786,"threshold_uncertainty_score":0.01639616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588903278711593,"score_gpt":0.2719304156464092,"score_spread":0.2560413828592933,"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."}}