{"id":"W3213956679","doi":"10.1002/etc.5251","title":"EcoToxXplorer: Leveraging Design Thinking to Develop a Standardized Web-Based Transcriptomics Analytics Platform for Diverse Users","year":2021,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Environment and Climate Change Canada; Université Laval; University of Saskatchewan; McGill University; St. Francis Xavier University","funders":"Genome Prairie; McGill University; Génome Québec; University of Saskatchewan; Environment and Climate Change Canada; Genome Canada; Government of Canada","keywords":"Analytics; Computer science; Web analytics; World Wide Web; Data science; The Internet; Web development; Web intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002215988,0.0002015842,0.0002020728,0.00001510695,0.0002155398,0.00003440043,0.0001375081,0.0002790299,0.00007841597],"category_scores_gemma":[0.00003082423,0.0002195558,0.00007738377,0.00005454483,0.0001006374,0.000006476675,0.0001199371,0.0001261016,0.000002545083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007828104,"about_ca_system_score_gemma":0.0001706687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.66914e-7,"about_ca_topic_score_gemma":0.000003435862,"domain_scores_codex":[0.9989915,0.00001694291,0.0002379177,0.000344194,0.00009254408,0.0003169186],"domain_scores_gemma":[0.9995267,0.00003462151,0.00006685247,0.0002067279,0.00001793191,0.0001471822],"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":[0.0003989417,0.00007881788,0.001064796,0.0000556572,0.0001516177,0.00001157509,0.0002627074,0.003007224,0.9893958,0.000009571464,0.002069239,0.003494029],"study_design_scores_gemma":[0.002900726,0.0001574917,0.0002854781,0.00002069636,0.00008505939,0.000039272,0.0009647377,0.004888572,0.9491041,0.0002238348,0.04089874,0.0004313244],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8948342,0.0003367861,0.1039163,0.0001993073,0.0001027023,0.0002507904,0.0001416946,0.00001264318,0.0002056246],"genre_scores_gemma":[0.9668325,0.0002150997,0.03024698,0.001774378,0.0001056767,0.00004900693,0.0004175733,0.00002676999,0.0003320222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07366928,"threshold_uncertainty_score":0.8953226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0172555388926494,"score_gpt":0.2208009209605094,"score_spread":0.20354538206786,"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."}}