{"id":"W6893384533","doi":"10.5281/zenodo.15732134","title":"MutSeqRData","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Rendering (computer graphics); Visualization; Data visualization; Software","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":[0.001611071,0.002878996,0.002146956,0.002903297,0.001404751,0.002722923,0.004297939,0.002365947,0.08843325],"category_scores_gemma":[0.005718107,0.001160157,0.001741135,0.004469524,0.0006324527,0.001673602,0.002460801,0.002829716,0.1609359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223748,"about_ca_system_score_gemma":0.002275878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01085704,"about_ca_topic_score_gemma":0.0194247,"domain_scores_codex":[0.9983062,0.0002672247,0.000193241,0.0006891846,0.0003301608,0.0002140019],"domain_scores_gemma":[0.9978899,0.0005823663,0.000229127,0.000694776,0.0004090212,0.000194873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001817815,0.00003941137,0.00108856,0.001140922,0.00007619609,0.00004852019,0.00005512748,0.0006907833,0.001080853,0.0009748237,0.990919,0.003703992],"study_design_scores_gemma":[0.0002894338,0.00003341765,0.002464259,0.0002004568,0.00006596018,0.0001131205,0.00006039959,0.0006434107,0.001820378,0.002693169,0.9915576,0.0000583722],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001711353,0.000051668,0.000296816,0.00002903242,0.00002718416,0.00001240636,0.9973279,0.0015328,0.0005509598],"genre_scores_gemma":[0.0003125091,0.00003424513,0.0005449784,0.00004703405,0.000004041018,0.00006775152,0.9981917,0.0004123924,0.000385438],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08843325,"threshold_uncertainty_score":0.2958387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01671484188302789,"score_gpt":0.2281528004132311,"score_spread":0.2114379585302032,"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."}}