{"id":"W4393662871","doi":"10.5281/zenodo.7392043","title":"Supplementary material for a usability evaluation of a semantic search for biological datasets","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Usability; Computer science; Information retrieval; World Wide Web; Human–computer interaction","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":[0.003790851,0.001495591,0.0006774273,0.003461839,0.0008782282,0.001659065,0.0009906476,0.0008961458,0.09981611],"category_scores_gemma":[0.01558406,0.0003429351,0.0008125555,0.003227245,0.0003308737,0.001149456,0.001612472,0.0008384471,0.04229102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001473749,"about_ca_system_score_gemma":0.001254307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007851419,"about_ca_topic_score_gemma":0.02505152,"domain_scores_codex":[0.9970129,0.0009770371,0.000477923,0.0004911504,0.0008596635,0.0001813396],"domain_scores_gemma":[0.9864305,0.00839482,0.0004033138,0.00162617,0.002680166,0.0004650589],"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":[0.0003818307,0.0005886687,0.004778359,0.001800261,0.0000846168,0.0001374718,0.000235777,0.001114887,0.001166437,0.00106615,0.9621896,0.02645588],"study_design_scores_gemma":[0.000826477,0.0003866052,0.03691099,0.0006062456,0.000126517,0.0006442438,0.0008828805,0.007826259,0.006430876,0.004980078,0.9402536,0.0001252253],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01068082,0.0002479586,0.005169303,0.0003236467,0.000146022,0.0006583154,0.9678221,0.007324758,0.007626962],"genre_scores_gemma":[0.01036271,0.00008365725,0.01186895,0.0002520609,0.00001855871,0.001906988,0.9710708,0.001004425,0.003431861],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09981611,"threshold_uncertainty_score":0.3339182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08542570881769637,"score_gpt":0.3367827754308616,"score_spread":0.2513570666131653,"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."}}