{"id":"W4406080583","doi":"10.1016/j.mex.2025.103155","title":"Development of a risk assessment software for cumulative effect","year":2025,"lang":"en","type":"article","venue":"MethodsX","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canadian Forest Service; Natural Resources Canada; U.S. Forest Service","keywords":"Risk assessment; Software; Engineering; Computer science","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":[0.001205857,0.000142099,0.0002544727,0.0000316583,0.0002127473,0.00001108081,0.0001624162,0.00006463518,0.0002344792],"category_scores_gemma":[0.0002991444,0.0001188989,0.00008893551,0.0002133816,0.0001331108,0.0001014194,0.0002042529,0.00009464593,0.00001602765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003524919,"about_ca_system_score_gemma":0.00003052793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007673731,"about_ca_topic_score_gemma":0.00002600459,"domain_scores_codex":[0.9988,0.0002586228,0.000272915,0.0002334949,0.0002204904,0.0002144445],"domain_scores_gemma":[0.9989351,0.0007076516,0.0001377417,0.0001591189,0.000006418275,0.00005397644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00005737974,0.0001999294,0.4031617,0.00005210322,0.0001192942,5.182812e-7,0.002348057,0.0003215317,0.01219871,0.00017878,0.0003579735,0.581004],"study_design_scores_gemma":[0.0009621078,0.0001112522,0.9337352,0.00003550122,0.00008620902,1.389831e-7,0.0002163541,0.0004151399,0.04695271,0.006206371,0.01108045,0.0001985896],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.532638,0.00001277293,0.4624466,0.00001937521,0.000133744,0.0004439577,0.00001738671,0.00002071655,0.00426745],"genre_scores_gemma":[0.2427545,0.000003575564,0.7565069,0.0000628428,0.000008495548,0.0001036085,0.000009680487,0.000008742138,0.0005417382],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5808054,"threshold_uncertainty_score":0.4848557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02394270371529382,"score_gpt":0.4010873651692017,"score_spread":0.3771446614539078,"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."}}