{"id":"W114833178","doi":"","title":"An addition structure on incidence matrices of a BIB design.","year":2006,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Pure mathematics","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":[0.0004577363,0.0005095588,0.0003012257,0.001199832,0.0008271005,0.001950797,0.0005175731,0.0003985499,0.01856557],"category_scores_gemma":[0.001868896,0.0003295358,0.0003253806,0.001257203,0.0007995638,0.001663761,0.001024854,0.001033519,0.004287532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006116119,"about_ca_system_score_gemma":0.0006245825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006476951,"about_ca_topic_score_gemma":0.001624314,"domain_scores_codex":[0.9993917,0.0001272483,0.00004808839,0.00008537917,0.0002341864,0.0001132832],"domain_scores_gemma":[0.9991195,0.000267469,0.0001259961,0.0001687419,0.0002211818,0.00009719111],"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":[0.0002163528,0.00009576861,0.0006343005,0.0001892454,0.00001858334,0.0003496055,0.0002541885,0.009289341,0.01816592,0.8611326,0.0105283,0.09912565],"study_design_scores_gemma":[0.00007654459,0.0003227205,0.0009083261,0.000134256,0.00004346099,0.00104644,0.0002312313,0.07051019,0.02847552,0.8317868,0.06640279,0.0000617296],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09278709,0.0004919064,0.7255684,0.0006696198,0.0005365924,0.000183196,0.0007250105,0.00114831,0.1778899],"genre_scores_gemma":[0.6932067,0.000788095,0.2412714,0.0005440483,0.0003186713,0.0002286492,0.001135738,0.0003660061,0.06214068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01856557,"threshold_uncertainty_score":0.06210798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006313987459908322,"score_gpt":0.2111465538335952,"score_spread":0.2048325663736868,"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."}}