{"id":"W24670144","doi":"","title":"Genetically Engineered Probes for Biomedical Applications","year":2006,"lang":"en","type":"article","venue":"Rural and Remote Health","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genetically engineered; Computer science; Biology; Computational biology; Biotechnology; Engineering; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005469098,0.0004715001,0.0003256329,0.000423245,0.0002840393,0.0007618092,0.0005693864,0.001183974,0.007029308],"category_scores_gemma":[0.000946585,0.0002560968,0.000418435,0.0003331298,0.0005197154,0.000508384,0.0005456824,0.001353911,0.002457672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004615832,"about_ca_system_score_gemma":0.0003745425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003838134,"about_ca_topic_score_gemma":0.0005205647,"domain_scores_codex":[0.999714,0.00006337005,0.00002116179,0.00006061859,0.0001008351,0.0000399923],"domain_scores_gemma":[0.99968,0.00009141021,0.00007858034,0.00007272707,0.00003829079,0.00003909072],"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":[0.0000863758,0.0001018935,0.0002082551,0.0002248213,0.00001942369,0.0001436168,0.00006056404,0.0007993028,0.9567024,0.009591657,0.002726647,0.02933513],"study_design_scores_gemma":[0.0001226061,0.001128907,0.00183679,0.0001254069,0.00008081835,0.0008480387,0.00008765356,0.006154992,0.7906013,0.006948905,0.1920069,0.00005765453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3006386,0.02416239,0.5795621,0.008484495,0.005407305,0.001819211,0.005927777,0.00714195,0.06685615],"genre_scores_gemma":[0.7184219,0.01109374,0.2264221,0.001664391,0.0002540251,0.002158987,0.0036047,0.0004398387,0.03594024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007029308,"threshold_uncertainty_score":0.02351534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008663565411678335,"score_gpt":0.2427236502923153,"score_spread":0.234060084880637,"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."}}