{"id":"W4403594579","doi":"10.1016/j.fertnstert.2024.07.633","title":"NON-INVASIVE BIOMARKERS FOR EMBRYO SELECTION IN IVF: UNVEILING SECRETED SIGNATURES FOR IMPLANTATION PREDICTION","year":2024,"lang":"en","type":"article","venue":"Fertility and Sterility","topic":"Reproductive Biology and Fertility","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Selection (genetic algorithm); Embryo; Andrology; Biology; Computational biology; Medicine; Cell biology; Computer science; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001098922,0.0007595211,0.000861817,0.0009837403,0.0002428554,0.001824833,0.0003258174,0.0009384709,0.0009005509],"category_scores_gemma":[0.001651803,0.0002452084,0.0004671514,0.0007295868,0.0003844764,0.0005855453,0.000579786,0.001002046,0.0004527565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001795006,"about_ca_system_score_gemma":0.000416699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002811393,"about_ca_topic_score_gemma":0.0005633965,"domain_scores_codex":[0.999438,0.0001450763,0.00003788351,0.0001264543,0.0001909219,0.00006167184],"domain_scores_gemma":[0.9993467,0.0002721985,0.0001707175,0.00004140097,0.0001093733,0.00005966334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002181261,0.000484451,0.1929773,0.001246836,0.000485722,0.0007377418,0.0003228351,0.001870837,0.611751,0.001160231,0.003953337,0.1828286],"study_design_scores_gemma":[0.0003179706,0.003716218,0.4543334,0.0009875826,0.001993098,0.005465301,0.001465722,0.05575417,0.4356836,0.008487639,0.03150909,0.000286358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9011852,0.05139772,0.03518241,0.001771997,0.00072532,0.0001981296,0.004127821,0.0003591481,0.005052163],"genre_scores_gemma":[0.9590365,0.01008275,0.02445349,0.001206709,0.0004653326,0.0001524476,0.001878825,0.00005308514,0.002670842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001824833,"threshold_uncertainty_score":0.005811691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02153048413810203,"score_gpt":0.2972185735272936,"score_spread":0.2756880893891915,"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."}}