{"id":"W154253029","doi":"","title":"On embedding partial unitals and large (k, n)-arcs","year":2002,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Embedding; Mathematics; Pure mathematics; Combinatorics; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0006972958,0.0007456299,0.0008291435,0.001484481,0.001875917,0.003950336,0.001180818,0.001286301,0.01151504],"category_scores_gemma":[0.006503065,0.0007257758,0.0005933187,0.002685136,0.003012164,0.007680514,0.003266519,0.002182417,0.001178899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001471144,"about_ca_system_score_gemma":0.0004162839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001178053,"about_ca_topic_score_gemma":0.002119187,"domain_scores_codex":[0.9991819,0.0003345412,0.00004132039,0.0001543255,0.0001276392,0.0001601331],"domain_scores_gemma":[0.9941182,0.00402321,0.0004764777,0.0006534047,0.0003045223,0.0004241141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001051315,0.00004002955,0.0004389953,0.00009161781,0.00001022572,0.0001697091,0.0004389675,0.005843864,0.001099393,0.9762224,0.002405158,0.01313453],"study_design_scores_gemma":[0.00001605868,0.00001727176,0.0002784176,0.00003349898,0.00001567881,0.000187241,0.0003162252,0.01947337,0.0009818227,0.9730783,0.00558593,0.00001622855],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4965223,0.002073317,0.2936283,0.003281063,0.0002748849,0.0001203868,0.0005867954,0.001076541,0.2024364],"genre_scores_gemma":[0.9246399,0.001067733,0.03662086,0.0003134732,0.000142935,0.0001057913,0.0003308772,0.0002709787,0.03650745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01151504,"threshold_uncertainty_score":0.03852171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009529900423714164,"score_gpt":0.2078367881897664,"score_spread":0.1983068877660522,"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."}}