{"id":"W4399724513","doi":"10.2139/ssrn.4866509","title":"Protein-Induced DNA Dumbell Amplification (Pinda) and its Applications to Food Hazards Detection","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"DNA; Computational biology; Computer science; Biology; Genetics","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":[0.0009941605,0.001022182,0.0008358127,0.0009216461,0.0004855882,0.0008647334,0.001198866,0.001557636,0.002472901],"category_scores_gemma":[0.001276943,0.0007261093,0.0004617124,0.001048883,0.0009379291,0.0007420884,0.001227925,0.001680955,0.001661521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000574978,"about_ca_system_score_gemma":0.000319512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002214327,"about_ca_topic_score_gemma":0.0004243994,"domain_scores_codex":[0.9986766,0.0003140247,0.00002975675,0.0006536024,0.000214342,0.0001117197],"domain_scores_gemma":[0.999369,0.0002580851,0.0001378077,0.0001245357,0.00006070653,0.00004984334],"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":[0.0001382705,0.00003742378,0.0002936968,0.0003749072,0.00002755722,0.0001459545,0.00006897683,0.0006843989,0.9748069,0.002275921,0.0002097826,0.02093627],"study_design_scores_gemma":[0.000007665415,0.0001746873,0.0003312918,0.00001376994,0.00001733812,0.000316981,0.00001723076,0.00448724,0.9882776,0.0008737731,0.005461846,0.00002065931],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1034931,0.009239342,0.875561,0.0004213634,0.000353375,0.000257873,0.0004674806,0.00387967,0.006326808],"genre_scores_gemma":[0.592524,0.005231085,0.3902127,0.0004373034,0.00009814619,0.0003905152,0.0007828217,0.0002967122,0.01002673],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002472901,"threshold_uncertainty_score":0.008272707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01270559600213794,"score_gpt":0.2799735304277077,"score_spread":0.2672679344255697,"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."}}