{"id":"W4410453369","doi":"10.53555/sfs.v10i3.3569","title":"Arachnid Silk Adhesion","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Silk-based biomaterials and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chandigarh University","keywords":"SILK; Adhesion; Polymer science; Materials science; Composite material","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":[0.0001354553,0.000455292,0.0001602748,0.0003375624,0.0003432682,0.0005459936,0.000191713,0.0003187004,0.003799215],"category_scores_gemma":[0.0002398915,0.0001355188,0.0002287748,0.0001938576,0.0001557692,0.0003854399,0.0005226008,0.0003671752,0.0008997477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002913367,"about_ca_system_score_gemma":0.0002007741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00104234,"about_ca_topic_score_gemma":0.001657945,"domain_scores_codex":[0.9998397,0.00001266743,0.0000125522,0.00002996285,0.00006366468,0.00004147847],"domain_scores_gemma":[0.9999433,0.000008775601,0.00001433789,0.000004636322,0.00001664558,0.00001236162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005621588,0.0000203812,0.002530685,0.001264378,0.00006174989,0.0005256275,0.0001867102,0.0003929909,0.9491305,0.002947988,0.001283437,0.0415993],"study_design_scores_gemma":[0.00001292162,0.000377114,0.04433464,0.0005827978,0.0001816263,0.001729856,0.0007222393,0.001901208,0.7768635,0.001369155,0.171881,0.00004390019],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8398919,0.08528119,0.006998844,0.0004447444,0.0004737523,0.00008668569,0.0008517816,0.0002243414,0.06574685],"genre_scores_gemma":[0.9694436,0.0172888,0.002544539,0.0001348981,0.00004026188,0.00003454844,0.000476751,0.00001706772,0.01001962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003799215,"threshold_uncertainty_score":0.01270968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1750086098341208,"score_gpt":0.3107442043180313,"score_spread":0.1357355944839106,"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."}}