{"id":"W4409600077","doi":"10.58414/scientifictemper.2025.16.1.04","title":"Measuring the research productivity on environmental toxicology: A scientometric study","year":2025,"lang":"en","type":"article","venue":"THE SCIENTIFIC TEMPER","topic":"Impact of AI and Big Data on Business and Society","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Environmental toxicology; Medicine; Economics; Toxicity","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.05576769,0.0001419599,0.0001960407,0.001075756,0.005167367,0.002531576,0.002971996,0.00005312548,0.0002567107],"category_scores_gemma":[0.005007604,0.00005730405,0.0001204885,0.01159732,0.002014573,0.0003505936,0.001029353,0.0004986832,0.0006340249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001426156,"about_ca_system_score_gemma":0.0002134807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004193277,"about_ca_topic_score_gemma":0.00003514682,"domain_scores_codex":[0.9923688,0.001360182,0.0003696146,0.0009433362,0.00438044,0.0005776004],"domain_scores_gemma":[0.9954564,0.001856555,0.00009180176,0.002254098,0.0002676914,0.00007348463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002525475,0.006306646,0.1696861,0.00001170902,0.0001538973,0.00001334711,0.0280296,0.0001880241,0.05419775,0.003749423,0.5016151,0.2357959],"study_design_scores_gemma":[0.000474058,0.0001891339,0.827332,0.00001577052,0.00001893688,0.000003074773,0.03612376,0.0001610011,0.003606927,0.004306383,0.1276078,0.000161193],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836715,0.0001425861,0.00002925979,0.009694193,0.002484611,0.0008920543,0.00002426716,0.00002252302,0.003038957],"genre_scores_gemma":[0.9611787,0.00000256966,0.000006243349,0.000238872,0.0001027259,0.00003804062,0.000001714804,0.000004900596,0.03842622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6576459,"threshold_uncertainty_score":0.9985039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4015733195642862,"score_gpt":0.4618272750804459,"score_spread":0.0602539555161597,"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."}}