{"id":"W4242828674","doi":"10.24908/iqurcp.8904","title":"Queen's Genetically Engineered Machine Team (QGEM): Nemoremediation","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genetically engineered; Population; Genetically modified organism; Biology; Homo sapiens; Biotechnology; Gene; Genetics; Archaeology; Geography","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":[0.001816348,0.0005165073,0.0003450755,0.0003639409,0.0007241803,0.001193,0.0009416873,0.0009156735,0.006326169],"category_scores_gemma":[0.001014599,0.0002772739,0.0004103426,0.0002581971,0.000626381,0.0009432651,0.001644677,0.001451392,0.002410645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00100404,"about_ca_system_score_gemma":0.001275799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001983861,"about_ca_topic_score_gemma":0.003322451,"domain_scores_codex":[0.9990651,0.0001159459,0.00003977319,0.0001727881,0.0004956583,0.0001106991],"domain_scores_gemma":[0.9993998,0.00005892371,0.00007922355,0.00008547421,0.0001398692,0.0002367383],"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":[0.00070269,0.0005175067,0.004192894,0.0002885333,0.00007184526,0.0004601871,0.0004282406,0.001977353,0.6133279,0.03607395,0.06632845,0.2756304],"study_design_scores_gemma":[0.0001811781,0.001175446,0.003123405,0.00007900907,0.00004182209,0.0004717638,0.0001116507,0.006786998,0.3356788,0.0029523,0.6493169,0.00008068972],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3386212,0.006818423,0.4894789,0.01927835,0.007163829,0.001341935,0.003284678,0.01423454,0.1197783],"genre_scores_gemma":[0.2688197,0.004075658,0.4317001,0.004448539,0.0002734397,0.0006864031,0.004545396,0.0021298,0.283321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006326169,"threshold_uncertainty_score":0.02116317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03914757487306498,"score_gpt":0.3073236990536007,"score_spread":0.2681761241805358,"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."}}