{"id":"W4416974110","doi":"10.1016/j.fertnstert.2025.07.1192","title":"BEYOND SUBJECTIVE GRADING: AI-POWERED TOOLS FOR MORE PRECISE BLASTOCYST EVALUATIONS","year":2025,"lang":"en","type":"article","venue":"Fertility and Sterility","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"CReATe Fertility Centre; University of Toronto","funders":"","keywords":"Infertility; Fertility; Human fertility; Blastocyst; Human reproduction; Reproductive medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003864052,0.0001695139,0.0002473464,0.00005456119,0.000169408,0.0001097201,0.0001273068,0.0001037266,0.00005897483],"category_scores_gemma":[0.0002655353,0.0001649766,0.00008541351,0.0001447694,0.0001075688,0.0002583875,0.00004584265,0.0001351102,0.000003152265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008192661,"about_ca_system_score_gemma":0.00003729041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002292933,"about_ca_topic_score_gemma":0.0001086649,"domain_scores_codex":[0.9989784,0.00004536428,0.0002988016,0.0003284498,0.0001130508,0.0002358863],"domain_scores_gemma":[0.9992163,0.0001868249,0.00001926268,0.0003706243,0.000132988,0.00007399585],"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":[0.01810772,0.001009035,0.02081514,0.004314994,0.000988461,0.000006344974,0.01257092,0.01445954,0.02237495,0.004940028,0.003848785,0.8965641],"study_design_scores_gemma":[0.0003720526,0.00006614924,0.8760519,0.0000472532,0.00005303298,7.358032e-7,0.0001861771,0.08907133,0.01112137,0.02106066,0.001742632,0.0002266791],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7523075,0.0004538353,0.2429029,0.0002122446,0.0004374544,0.0008882082,0.0001726704,0.0001428889,0.002482221],"genre_scores_gemma":[0.9989071,0.00001324965,0.0005370154,0.00008691513,0.00001742306,0.0001681069,0.00003231171,0.000009680855,0.0002281448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8963374,"threshold_uncertainty_score":0.6727549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02920411036038369,"score_gpt":0.3120908567290684,"score_spread":0.2828867463686847,"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."}}