{"id":"W1984653158","doi":"10.1163/156856206778667488","title":"Interplay of biomaterials and micro-scale technologies for advancing biomedical applications","year":2006,"lang":"en","type":"review","venue":"Journal of Biomaterials Science Polymer Edition","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Charles Stark Draper Laboratory","keywords":"Nanotechnology; Microelectronics; Scale (ratio); Tissue engineering; Engineering; Computer science; Materials science; Biomedical engineering","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":[0.0009420566,0.0008478606,0.001184882,0.002560368,0.000340984,0.001240712,0.0007566931,0.001401177,0.003155495],"category_scores_gemma":[0.0006309653,0.0004191002,0.0005100114,0.002267948,0.0007091008,0.002085154,0.0007842657,0.001671429,0.003694157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006734966,"about_ca_system_score_gemma":0.0008997614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000337804,"about_ca_topic_score_gemma":0.0006883286,"domain_scores_codex":[0.9994366,0.00007321264,0.00005946948,0.00006458867,0.0003303276,0.00003584248],"domain_scores_gemma":[0.9995874,0.0002137537,0.00004453155,0.00002553552,0.00009806582,0.00003073771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005194685,0.0001528303,0.0001884023,0.01182585,0.00005795698,0.000412281,0.0001230713,0.0008381418,0.03957076,0.0298682,0.01164675,0.9052637],"study_design_scores_gemma":[0.00002313108,0.000191039,0.0007950001,0.001619259,0.00005206692,0.002353086,0.00008712635,0.0003552622,0.01471051,0.01141559,0.9683612,0.00003667116],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004989383,0.9925252,0.00218178,0.0004359745,0.0003547944,0.00001953442,0.00001150429,0.00002521753,0.003947028],"genre_scores_gemma":[0.002680964,0.990631,0.003954254,0.0002790768,0.0003118287,0.00002766193,0.00001944984,0.000005593449,0.002090134],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003155495,"threshold_uncertainty_score":0.01055622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01567404419056943,"score_gpt":0.3493116090173449,"score_spread":0.3336375648267754,"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."}}