{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005974757,0.00009244467,0.000219428,0.0002187022,0.000194109,0.0002222789,0.0005589931,0.00004781626,0.0003463727],"category_scores_gemma":[0.0004581925,0.0000654781,0.0000460898,0.001251977,0.0004046833,0.0005185643,0.00006917236,0.00006161958,0.000118753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002918204,"about_ca_system_score_gemma":0.0001536853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003294072,"about_ca_topic_score_gemma":0.0002802475,"domain_scores_codex":[0.9983403,0.000234518,0.0005254308,0.0001712085,0.0004627089,0.000265807],"domain_scores_gemma":[0.9989643,0.0003912375,0.0003265481,0.0001219679,0.0001271257,0.00006878648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003709779,0.00003922517,0.309708,0.000008239024,0.000001154602,0.00001436527,0.0001449812,0.00009375773,0.6831477,0.00006384648,0.006257023,0.0004845897],"study_design_scores_gemma":[0.0001812867,0.0002107005,0.801899,0.00004218001,0.000002569358,0.00002199223,0.0002820632,0.00002944466,0.1946433,0.0009156587,0.001653127,0.0001186782],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976934,0.00005381665,0.00002177629,0.0009543655,0.0008591591,0.00006194825,0.00002605671,0.00003006708,0.0002994168],"genre_scores_gemma":[0.9988869,0.00007159168,0.0007600033,0.00007798096,0.0001044611,0.00000470743,0.000002813332,0.000005294578,0.00008628983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.492191,"threshold_uncertainty_score":0.3792538,"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."}}