{"id":"W4403979562","doi":"10.5206/mt.v4i3.21093","title":"The Extended Watson—Wong—Wyman Lemma in Maple","year":2024,"lang":"en","type":"article","venue":"Maple Transactions","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Maple; Watson; Lemma (botany); Mathematics; Computer science; Botany; Artificial intelligence; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007114551,0.0001329956,0.0001236323,0.0002459904,0.000366785,0.0007237559,0.0008652337,0.00005749426,0.0004895465],"category_scores_gemma":[0.00003876705,0.0001003127,0.00009589808,0.001337791,0.00008346912,0.0004002117,0.00003376435,0.0004035032,0.0004418397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009516899,"about_ca_system_score_gemma":0.0001688379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001186238,"about_ca_topic_score_gemma":0.0003086818,"domain_scores_codex":[0.9982218,0.0001598642,0.00029971,0.0004190082,0.0004716782,0.0004279037],"domain_scores_gemma":[0.9987319,0.0004149673,0.00001805555,0.0006527413,0.00006860197,0.0001137928],"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":[0.0000170318,0.0002842669,0.0000267027,0.0001018318,0.0001189162,0.0002489334,0.002716647,0.01798696,0.0004403426,0.1458333,0.008843687,0.8233814],"study_design_scores_gemma":[0.0001968019,0.00003109652,0.0005033395,0.00001906843,0.000006723124,0.00002958394,0.00008255745,0.8479108,0.0004574,0.004435316,0.1461804,0.0001469648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000127015,0.0004949973,0.9836717,0.01044346,0.0009010487,0.0002610503,0.00001155904,0.000304914,0.003784231],"genre_scores_gemma":[0.776404,0.0009795346,0.1519581,0.0002783131,0.0002296071,0.0005015474,0.00001599165,0.00008235411,0.06955053],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8317136,"threshold_uncertainty_score":0.6979194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01607905670076865,"score_gpt":0.2840969718976853,"score_spread":0.2680179151969167,"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."}}