{"id":"W6983518923","doi":"","title":"Modelling compounding across languages with analogy and composition","year":2025,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Essential Oils and Antimicrobial Activity","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Compounding; Analogy; Composition (language); Word (group theory); Process (computing); Computational model; Analogical reasoning; Component (thermodynamics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006030947,0.0001481199,0.0001754352,0.00001505949,0.0003020607,0.001014665,0.0001413773,0.00007520357,0.00003728004],"category_scores_gemma":[0.000006085157,0.00006248843,0.00005022205,0.0002973463,0.0000906121,0.001262216,0.0001322593,0.0001780387,0.0000279225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007611194,"about_ca_system_score_gemma":0.000006439221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003164248,"about_ca_topic_score_gemma":0.00001502119,"domain_scores_codex":[0.9991842,0.00003545186,0.0001450398,0.0002806564,0.00009192766,0.0002627259],"domain_scores_gemma":[0.9996772,0.0001268388,0.00005246293,0.00004219498,0.00001786359,0.00008346455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007655692,0.0008059387,0.500266,0.00021859,0.00017889,0.000127858,0.0000814651,0.0006805697,0.3765913,0.01013264,0.001183653,0.1089676],"study_design_scores_gemma":[0.004844332,0.001746,0.2214983,0.003307498,0.0002640639,0.0003037433,0.001710036,0.01385965,0.3484459,0.04859347,0.3500579,0.005369099],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931875,0.0001142714,0.0003249559,0.001078294,0.00003284905,0.00009700088,0.0006386644,0.0001319163,0.004394477],"genre_scores_gemma":[0.998643,0.00001974501,0.0002298601,0.000370157,0.0000643892,0.000002898493,0.0004312403,0.000002058779,0.0002366186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3488743,"threshold_uncertainty_score":0.9784434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01130858317984004,"score_gpt":0.2171077454434881,"score_spread":0.2057991622636481,"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."}}