{"id":"W4366815133","doi":"10.1093/sysbio/syad025","title":"Formalizing Invertebrate Morphological Data: A Descriptive Model for Cuticle-Based Skeleto-Muscular Systems, an Ontology for Insect Anatomy, and their Potential Applications in Biodiversity Research and Informatics","year":2023,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Academy of Finland; Deutsche Forschungsgemeinschaft; Helsingin Yliopisto","keywords":"Ontology; Biology; Open Biomedical Ontologies; Interoperability; Computer science; Evolutionary biology; Information retrieval; Ontology-based data integration; Ontology alignment; Semantic Web; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002343677,0.0007376739,0.0005575641,0.003554368,0.001112029,0.003713057,0.002504119,0.001119257,0.001595175],"category_scores_gemma":[0.002459026,0.0006214858,0.002501983,0.00246005,0.003019805,0.006765857,0.002167588,0.00204912,0.0007562231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002487681,"about_ca_system_score_gemma":0.003143889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01342065,"about_ca_topic_score_gemma":0.01564704,"domain_scores_codex":[0.9988903,0.0001861622,0.0002802007,0.0002346064,0.0003334003,0.00007532191],"domain_scores_gemma":[0.9987271,0.0004123241,0.0002094034,0.0002951242,0.0002533104,0.0001025804],"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":[0.00004186499,0.0000491055,0.002115442,0.0004749114,0.00005271377,0.0006134983,0.002226056,0.01329631,0.00712816,0.9236675,0.004358423,0.04597595],"study_design_scores_gemma":[0.0000395214,0.00009122755,0.002487213,0.0007723065,0.0001629247,0.001245998,0.001299436,0.1229253,0.00802902,0.4569204,0.4058901,0.0001364842],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01218873,0.0008222547,0.9748399,0.0009587304,0.00009438914,0.0002253618,0.003465235,0.001055577,0.00634984],"genre_scores_gemma":[0.1046671,0.00170224,0.8783135,0.0004473094,0.00009758231,0.0007334696,0.008915422,0.0003359971,0.004787276],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01342065,"threshold_uncertainty_score":0.02668506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2433630507983301,"score_gpt":0.3531661496033901,"score_spread":0.10980309880506,"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."}}