{"id":"W2950183056","doi":"10.2139/ssrn.3345274","title":"The Blood Compatibility Challenge","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Compatibility (geochemistry); Engineering","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":[0.007238292,0.0004333827,0.0008951196,0.0011327,0.0012708,0.005175113,0.001396987,0.006093151,0.01932021],"category_scores_gemma":[0.009801677,0.0003730898,0.0004838345,0.00055688,0.004777473,0.005854257,0.002964546,0.008875428,0.006853005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476419,"about_ca_system_score_gemma":0.001796714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006167573,"about_ca_topic_score_gemma":0.0006208976,"domain_scores_codex":[0.9969572,0.0008951374,0.0001071026,0.0004583154,0.001311845,0.000270417],"domain_scores_gemma":[0.9939739,0.003530459,0.0003547387,0.0004633238,0.0009813631,0.0006961697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002078222,0.0001355787,0.0007581762,0.0005075479,0.00004103122,0.0008852143,0.0005549907,0.000300531,0.007395767,0.5569375,0.2193732,0.2129027],"study_design_scores_gemma":[0.00003061509,0.0001652733,0.0004564601,0.000410732,0.00002026678,0.002745276,0.0003748234,0.0005635701,0.004028257,0.147076,0.8440967,0.00003212009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01425755,0.2417262,0.02575718,0.5337419,0.02139663,0.00005670874,0.0002962156,0.00026933,0.1624983],"genre_scores_gemma":[0.2887385,0.2224294,0.02234081,0.2918394,0.05688711,0.0003616237,0.0004737755,0.0004596125,0.1164699],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01932021,"threshold_uncertainty_score":0.06463259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007552696331954371,"score_gpt":0.2415883314054503,"score_spread":0.2340356350734959,"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."}}